Recently, a significant amount of research has been devoted to soft robots. Artificial muscles belong to the most important components of soft robots. Dielectric elastomer actuators (DEAs) represent the technology that comes closest to the capabilities of a natural muscle, making them the best candidates for artificial muscles in robotics and prosthetics applications. To develop these applications, an analysis of DEAs in a test bench must be possible. It is important that the environmental conditions are known, and all components are specified, which is not the case in most publications. This paper focuses on the development of a real-time test bench for DEAs which provides environmental conditions and all components that are specified. Its goal is to open up the research field of dielectric elastomer actuators or soft robots. The stacked DEA used is powered by a high-voltage amplifier, which can be controlled via a real-time block diagram environment together with a data acquisition (DAQ) device. The response of the actuator is measured with a laser triangulation sensor. Furthermore, information about the applied voltage, the operating current, the temperature, and the humidity are collected. It was demonstrated that the selected laser sensor is a suitable device for this application. Moreover, it was shown that the selected high-voltage amplifier is adequate to power a DEA. However, the DAQ is not fast enough to measure the actuator current. It was demonstrated that housing keeps environmental conditions constant, is transportable, and offers the flexibility to investigate different DEAs.

This work describes the parameter identification of servo systems using the least squares of orthogonal distances method. The parameter identification problem was reconsidered as data fitting to a plane, which in turn corresponds to a nonlinear minimization problem. Three models of a servo system, having one, two, and three parameters, were experimentally identified using both the classic least squares and the least squares of orthogonal distances. The models with two and three parameters were identified through numerical routines. The servo system model with a single parameter only considered the input gain. In this particular case, the analytical conditions for finding the critical points and for determining the existence of a minimum were presented, and the estimate of the input gain was obtained by solving a simple quadratic equation whose coefficients depended on measured data. The results showed that as opposed to the least squares method, the least squares of orthogonal distances method experimentally produced consistent estimates without regard for the classic persistency-of-excitation condition. Moreover, the parameter estimates of the least squares of orthogonal distances method produced the best tracking performance when they were used to compute a trajectory-tracking controller.

Composite state convergence is a novel scheme applied for the bilateral control of a telerobotic system. The scheme offers an elegant design procedure and employs only three communication channels to establish synchronization between a single-master and a single-slave robotic system. This paper expands the capability of the composite state convergence scheme to accommodate any number of master and slave systems and proposes a disturbance observer-based composite state convergence architecture where k-master systems can cooperatively control l-slave systems in the presence of uncertainties. A systematic method is presented to compute the control gains while observer gains are determined in a standard way. To validate the proposed architecture, MATLAB simulations are performed on symmetric and asymmetric arrangements of single-degree-of-freedom teleoperation systems. Finally, experimental results are obtained using Quanser’s Qube-Servo systems in QUARC/Simulink environment.

Control systems influence our society enormously. Although they are invisible to most users, they
are essential to the functioning of almost all devices, be they basic household appliances, aircraft or
nuclear power plants. A common denominator among those different applications of control is the
need to influence or modify the behavior of dynamical systems to achieve specified goals. In this
context, one of the main objective of Artificial Intelligence is to solve complex control problems with
high-dimensionality of observation spaces or system models which are unavailable. Recent research
has shown that Deep Learning techniques can be combined with Reinforcement Learning methods to
learn useful representations allowing to solve the problems mentioned above. In particular, due to
the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has become one of the
most important and useful new technology in Control Engineering. It is a type of Machine Learning
technique in which a computer agent learns to perform a specific task by replacing the classic controller of the traditional control, through these repeated trials and error interactions with a dynamic
environment by selecting control inputs sequence based on measured outputs. This thesis intends to
provide an in-depth introduction of Deep Learning using Neural Networks combined with Reinforcement Learning methods and then apply them to learn an intelligent controller able to meet specific
system requirements without any kind of human supervision. In particular, the application of Deep
Deterministic Policy Gradient (DDPG) model-free method to autonomous control such as DC Motor
speed control to an inverted pendulum will be presented based on Reinforcement Learning MATLAB
Toolbox.

The increasing need for sharing workspace and interactive physical tasks between robots and humans has raised concerns regarding safety of such operations. In this regard, controllable clutches have shown great potential for addressing important safety concerns at the hardware level by separating the high-impedance actuator from the end effector by providing the power transfer from electromagnetic source to the human. However, the existing clutches suffer from high power consumption and large-weight, which make them undesirable from the design point of view. In this paper, for the first time, the design and development of a novel, lightweight, and low-power torque-adjustable rotary clutch using electroadhesive materials is presented. The performance of three different pairs of clutch plates is investigated in the context of the smoothness and quality of output torque. The performance degradation issue due to the polarization of the insulator is addressed through the utilization of an alternating current waveform activation signal. Moreover, the effect of the activation frequency on the output torque and power consumption of the clutch is investigated. Finally, a time-dependent model for the output torque of the clutch is presented, and the performance of the clutch was evaluated through experiments, including physical human-robot interaction. The proposed clutch offers a torque to power consumption ratio that is six times better than commercial magnetic particle clutches. The proposed clutch presents great potential for developing safe, lightweight, and low-power physical human-robot interaction systems, such as exoskeletons and robotic walkers.

Dopaminergic replacement therapies (e.g. levodopa) provide limited to no response for
axial motor symptoms including gait dysfunction and freezing of gait (FOG) in
Parkinson’s disease (PD) and Richardson’s syndrome progressive supranuclear palsy
(PSP-RS) patients. Dopaminergic-resistant FOG may be a sensorimotor processing issue
that does not involve basal ganglia (nigrostriatal) impairment. Recent studies suggest that
spinal cord stimulation (SCS) has positive yet variable effects for dopaminergic-resistant
gait and FOG in parkinsonian patients. Further studies investigating the mechanism of
SCS, optimal stimulation parameters, and longevity of effects for alleviating FOG are
warranted. The hypothesis of the research described in this thesis is that mid-thoracic,
dorsal SCS effectively reduces FOG by modulating the sensory processing system in gait
and may have a dopaminergic effect in individuals with FOG. The primary objective was
to understand the relationship between FOG reduction, improvements in upper limb
visual-motor performance, modulation of cortical activity and striatal dopaminergic
innervation in 7 PD participants. FOG reduction was associated with changes in upper
limb reaction time, speed and accuracy measured using robotic target reaching choice
tasks. Modulation of resting-state, sensorimotor cortical activity, recorded using
electroencephalography, was significantly associated with FOG reduction while
participants were OFF-levodopa. Thus, SCS may alleviate FOG by modulating cortical
activity associated with motor planning and sensory perception. Changes to striatal
dopaminergic innervation, measured using a dopamine transporter marker, were
associated with visual-motor performance improvements. Axial and appendicular motor
features may be mediated by non-dopaminergic and dopaminergic pathways, respectively.
The secondary objective was to demonstrate the short- and long-term effects of SCS for
alleviating dopaminergic-resistant FOG and gait dysfunction in 5 PD and 3 PSP-RS
participants without back/leg pain. SCS programming was individualized based on which
setting best improved gait and/or FOG responses per participant using objective gait
analysis. Significant improvements in stride velocity, step length and reduced FOG
frequency were observed in all PD participants with up to 3-years of SCS. Similar gait
and FOG improvements were observed in all PSP-RS participants up to 6-months. SCS is
iii
a promising therapeutic option for parkinsonian patients with FOG by possibly
influencing cortical and subcortical structures involved in locomotion physiology.

Robot-assisted arthroscopic surgery is transforming the tradition in orthopaedic surgery. Compliance and stability are essential features that a surgical robot must have for safe physical human-robot interaction (pHRI). Surgical tools attached at the robot end-effector and human-robot interaction will affect the robot dynamics inevitably. This could undermine the utility and stability of the robotic system if the varying robot dynamics are not identified and updated in the robot control law. In this paper, an integrated framework for robot impedance control and nonlinear disturbance observer (NDOB)-based compensation of uncertain dynamics is proposed, where the former ensures compliant robot behavior and the latter compensates for dynamic uncertainties when necessary. The combination of impedance controller and NDOB is analyzed theoretically in three scenarios. A complete simulation and experimental studies involving three common conditions are then conducted to evaluate the theoretical analyses. A preliminary pHRI application on arthroscopic surgery is designed to implement the proposed framework on a robotic surgeon-assist system and evaluate its effectiveness experimentally. By integrating impedance controller with NDOB, the proposed framework allows an accurate impedance control when dynamic model inaccuracy and external disturbance exist.

Biomimetic robot systems have captured the attention of researchers for the past two decades. Along with biomimetic systems, the implementation of soft robotic arms has emerged and studied. Teleoperation of such biomimetic soft robots, i.e., a biomimetic squid robot, is still an open area of research. This study aims to initiate the development of a teleoperation system, which has multi-master multi-slave with dissimilar master-slave kinematics, to be adapted for the operation of an underwater biomimetic squid robot. The communication between the slave robot, which is the biomimetic squid robot’s soft arms, and the master system on the ground is estimated to have limited bandwidth. To overcome this problem, the model-mediation technique is selected to be adapted. The abstract information received from the slave side is used for regenerating the slave environment on the master side. The human operator uses two haptic devices to manipulate the four soft arms of this biomimetic robot via interacting with this regenerated model on the master side. The models of the biomimetic robot’s soft arms are developed by using the constant-curvature approach. While this study is limited in the sense that the slave side regeneration is previously completed on an ideally received signal even before the teleoperation is initiated, the teleoperation of 4 soft arms with two haptic devices is investigated. 4 different control strategies are formulated and evaluated on test subjects. The performances of the test subjects are evaluated based on their task completion duration, accuracy, and feedback received from their questionnaire answers. The primary investigation conducted is for the ergonomic use of teleoperation systems. Another evaluation is carried out to understand the influence of haptic feedback in telepresence. The evaluation results clearly indicate that the haptic feedback has improved the telepresence. The position-to-position mapping produced shorter task completion durations with worse accuracy relative to the position-to-velocity mapping.

This research concerns a novel attitude stabilization structure for a ducted-fan aerial robot to work against modeling error and strong external transient disturbance, and it focuses on two main control targets: modeling error compensation, and the improvement of disturbance resistance along the rolling channel. For the first research objective, we proposed an adaptive nominal controller with the reconfigurable control law design based on the estimation of the modeling error found in the closed-loop. Results of simulations and corresponding flight tests verified that the proposed adaptive control structure is robust against both constant and time-varying modeling error. For the other research objective, a SAC (stability augmentation structure) was devised based on the CMG (control moment gyroscope) theory in order to provide extra moment which effectively withstands the transient disturbance beyond the CDG (critical disturbance gain). Furthermore, we studied the corresponding controller for the SAC via the SMC (sliding mode control) theory, while the working mechanism and performance of the SAC were verified through a specially devised prototype.

In this paper, Motion planning and control of a differential drive robot in a supervised environment is presented. Differential drive robot is a mobile robot with two driving wheels in which the overall velocity is split between left and right wheels. Kinematic equations are derived and implemented in Simulink to observe the theoretical working principle of the robot. A proportional controller is designed to control the motion of the robot, which is later implemented on a physical robot. Combination of linear velocity and orientation generates individual wheel velocities which are sent to the robot by wireless communication for its motion.

This paper proposes a novel two-stage method for the design of a suboptimal model-matching controller in an output feedback closed-loop system (OFCLS) using the concept of squared magnitude function (SMF). A streamlined procedure for selection of a reference model, based on a linear quadratic regulator (LQR) with integral action (LQRI) having optimum values for the elements of the weighting matrices and the degree of interaction is proposed. The degrees of the numerator and denominator polynomials of the elements of the OFCLS transfer function matrix (TFM) are obtained from those of the plant and the chosen controller structure. In the first stage of the controller design, taking the LQRI-based closed-loop system (LCLS) as a reference model, the OFCLS is obtained using the approximate model-matching (AMM) technique based on the SMF concept. The approximation method involves a higher-order approximation for stable multiple-input-multiple-output (MIMO) lower-order systems. In the second stage, controller parameters are obtained using the exact model-matching (EMM) method with information about the OFCLS and plant TFMs. The proposed controller design method outperforms the method presented in the literature on integral squared error index. The simulation and experimental results illustrate the effectiveness of the proposed method.

In this work, an Active Disturbance Rejection Control scheme for a Laser Beam Stabilization system is presented in a pragmatic way. First, a Linear Extended State Observer is designed, which allows estimating external disturbances, non-model dynamics, and the transverse displacement speed of the beam. Subsequently, a control law is proposed for regulation and tracking tasks. The stability analysis in the Input-to-State-Stability framework shows that the closed-loop system, plant-observer-controller is stable when the total disturbance is viewed as the input, and the state is the beam position error. This analysis presents new perspectives to a now-classic result. The experimental results show the performance of the control scheme. Using the L2 norm and the Integral of the Squared Error, the closed-loop performance is evaluated and compared with three controls generally used in this type of systems: PID, observer based state feedback, and linear quadratic gaussian regulator.

The following work contains an experimental method for identifying dynamic friction in a DC servomotor, whose identification and subsequent compensation is highly important. Friction has characteristics that are difficult to equate and for this reason it becomes very important and necessary to identify nonlinearities and subsequently compensate them. In this paper, based on the DC motor equation using Newton’s law of motion, feasible models are presented and friction is measured and analyzed through Matlab and a Quanser data acquisition card. Nonlinear dynamic friction torque is used and compared with the experimental results of a real servomotor.

For the depth estimation problem in the image-based visual servoing (IBVS) control, this paper proposes a new observer structure based on Kalman filter (KF) to recover the feature depth in real time. First, according to the number of states, two different mathematical models of the system are established. The first one is to extract the depth information from the Jacobian matrix as the state vector of the system. The other is to use the depth information and the coordinate point information of the two-dimensional image plane as the state vector of the system. The KF is used to estimate the unknown depth information of the system in real time. And an IBVS controller gain adjustment method for 6-degree-of-freedom (6-DOF) manipulator is obtained using fuzzy controller. This method can obtain the gain matrix by taking the depth and error information as the input of the fuzzy controller. Compared with the existing works, the proposed observer has less redundant motion while solving the Jacobian matrix depth estimation problem. At the same time, it will also be beneficial to reducing the time for the camera to reach the target. Conclusively, the experimental results of the 6-DOF robot with eye-in-hand configuration demonstrate the effectiveness and practicability of the proposed method.

Human perceptual sensitivity of various types of forces, e.g.,stiffness and friction, is important for surgeons during robotic surgeries such as needle insertion and palpation. However, force feedback from robot end-effector is usually a combination of desired and undesired force components which could have an effect on the perceptual sensitivity of the desired one. In presence of undesired forces, to improve perceptual sensitivity of desired force could benefit robotic surgical outcomes. In this paper, we investigate how users’ perceptual sensitivity of friction and stiffness can be improved by taking advantage of kinematic redundancy of a user interface. Experimental results indicated that the perceptual sensitivity of both friction and stiffness can be significantly improved by maximizing the effective manipulability of the redundant user interface in its null space. The positive results provide a promising perspective to enhance surgeons’ haptic perceptual ability by making use of the robot redundancy.

A distributed control policy is designed for a group of Euler-Lagrange (EL) agents in a leader-follower based communication network with time-varying delays. The non-singular terminal sliding mode control (NTSMC) policy is integrated with mixed-type feedback and time-varying, adaptive control parameters. The control gain and proportions of feedback with and without estimated self-delays are tuned online with fuzzy logic control (FLC). The total and maximum tracking errors of a group of EL agents are assessed to demonstrate an improvement in synchronization performance with the proposed NTSMC+FLC approach compared to the NTSMC approach with constant parameters. Simulation and experimental results of a group of Phantom Omni manipulators are presented to validate the proposed control policy.

This paper presents the implementation of a position-torque control law for a 6DOF Stewart platform for tracking trajectories through its end-effector. First, the kinematics and a configuration description are depicted. Then, a control scheme is suggested and implemented using a Quanser data acquisition card that has compatibility with Matlab Simulink in order to control the linear positioners of the robot. The use of these elements merges a simple but rewarding control of this parallel robot towards a new scheme of technologic incorporation for aerospace applications which make use of the Stewart platform as a motion generator.

Ludibot, a mobile robot based on the Kinect v2 device, seeks to take advantage of human-machine gestural interaction for foreign language learning purposes. This project combines robotics with game studies and language and culture teaching to develop an interaction platform and playful applications for formal and informal language learning situations. This paper details the components of Ludibot and discusses the main aspects related to the control of the interactive human-robot mobile interface. Subsequently, it presents the structure and the control law of the interface and describes the first game developed, focused on the playful learning of vocabulary related to body parts in French. The preliminary results of the experimental tests reveal a high pedagogical potential, related to the novel and interactive character of the developed tools, whose use is possible to learn quickly and intuitively. Ludibot also has a high potential for adaptation in terms of the languages used, the linguistic level of the users, the degree of formality of the learning context, the possible special needs of the players, among others. However, there are still tests to be carried out in real situations, with Spanish-speaking high school students, in the classroom and in the media library. Planned for the beginning of the 2020-2021 school year, these tests had to be postponed due to the global health contingency. The main originality of Ludibot lies in the
deliberately multidisciplinary approach chosen, as well as in the possibility of providing effective but simple, adaptable and affordable technological tools, in order to promote the critical dissemination of new learning paradigms.

The movement in the horizontal plane for a quadrotor is achieved by the attitude adjustment in roll and pitch axes. Hence, essentially, the quadrotor dynamics can be described by a fourth-order equation. Different from the traditional cascade controllers, a controller design method based on the fourth-order model directly is presented. Since the first- and second-order time derivatives of the total thrust are necessary in the attitude controller design, an extended state observer is introduced. Rigorous theoretical proof, numerical simulation and experimental results are presented to validate the proposed controller.

Closed-loop functional electrical stimulation (FES) control methods are developed to enable motorized assistive split-crank (i.e., a cycle without mechanical coupling between the lower limbs) cycling for rehabilitation efforts for people with lower limb movement disorders. The non-dominant side tracks a desired range of cadence and the dominant side tracks a range of position offsets centered around the position of the non-dominant side. A multi-level switched system with switched control objectives is applied to both sides of the cycle-rider system. Assistive, uncontrolled, and resistive modes for the dominant and non-dominant subsystems are based on position and cadence, respectively. Global exponential tracking to upper and lower bounds of an uncontrolled desired region is proven for each side via Lyapunov-based analysis using switched system methods. Experiments on both able-bodied participants and participants with neuromuscular conditions show the performance of the switched control system for split-crank FES-cycling. From volitional to controlled pedaling in able-bodied participants, average RMS cadence error of the non-dominant, RMS position error of the dominant,
and cadence differential between the two legs improved by 76.2%, 65.3%, and 58.0%, respectively. On average, experiments on participants with neuromuscular conditions resulted in RMS errors that were 45.8%, 92.6%, and 52.0% higher than controlled trials on able-bodied participants, but 65.3%, 33.3%, and 36.3% lower than volitional-only trials of able-bodied participants.

Flexible robots are subject of many research-works since their advantages in terms of safety, compliance, low energy consumption, manoeuvrability, high payload to manipulator weight ratio, low cost, and high speed. However, the flexibility of manipulator’s links or joints and the under-actuation leads to complexity in the modelling and control. To deal with this problem, a sliding mode control is designed and applied to a presented model of the system. So, this paper presents the modelling of flexible joint manipulator, the design of adequate sliding mode controller which can stabilize the flexible joint manipulator. The robust tracking performance will be proved in the simulation.

Fluid-driven soft grippers possess conformable grasping characteristics that differ from their rigid counterparts. Despite advances, their inherent low-stiffness due to constituent materials causes them to be inferior in many high-load applications. Existing fabrication methods of soft grippers that mostly rely on molding silicone elastomers, despite being simple, are not easily scalable. This article presents the design of a soft robotic fabric gripper that can be fabricated by a facile and highly scalable process of apparel engineering. The proposed robotic gripper features a multi-fingered design that comprises hydraulic-driven, sheet-shaped fabric bending actuators. Its performance is enhanced by incorporating a bio-inspired gecko adhesive and a thermo-responsive variable stiffness filament. Experimental studies demonstrate that adding the variable stiffness filament and gecko adhesive improves the holding force of the gripper up to 655 % and 507 % in the gripping and pull-out configurations, respectively. The variable stiffness filament features a relatively good cooling speed of only 31 s by ambient cooling. A simple analytical model was also developed to characterize the deformation of the fabric bending actuators. To monitor the gripper bending motion, a new soft fabric sensor comprising a conductive composite of liquid metal and carbon particles was developed. The sensor was configured in a sheet-like shape and can be easily integrated into the gripper, which has been usually absent for other fabric grippers. The materials employed by this gripper design are commercially available for a reasonable budget, enabling the gripper to be both cost-effective and have potential applications where both gentle grasping and high load capacity are required.

The interaction between an elastic structure and electrodynamic shakers commonly exists in Ground Flutter Simulation Tests (GFST) with multi-point excitations, causing a considerable discrepancy between the practical excitation forces and desired ones. To investigate the excitation force characteristics on a cantilever beam excited by a voltage-sourced electrodynamic shaker, the coupled shaker-beam system is modeled to derive the excitation force formula using Hamilton’s principle and Galerkin’s approach. Simulation results using the multi-mode beam model coupled with the shaker model are in good agreement with experimental results, verifying that the proposed multi-mode method can accurately predict the excitation force. Furthermore, parametric studies show that the influence of system parameters on the excitation force is related to the shaker's operating mode. Unlike in current mode of shaker, when the beam resonant frequency approaches the suspension frequency of shaker armature, the variation of excitation force amplitude in voltage mode is no longer minimal. Meanwhile, if the exciting point in the GFST is located far away from the modal node, it is essential to compensate the force because the accuracy of tests can be reduced dramatically. The coupled shaker-beam model proposed in this paper can provide the basis for compensation measures.

This paper considers a transportation system consisting of a quadrotor with a cable-suspended payload. The main focus of this paper is to investigate the effect of polynomial trajectories on the vibration of the cable-suspended payload and to show which polynomial trajectory results in less vibration. A mathematical analysis and a parametric study were carried out to investigate the effect of the degree of the polynomial trajectory on its kinematic behavior. A conjecture relates the degree of the polynomial trajectory and its kinematic behavior to the corresponding payload vibration was introduced. The base excitation model of vibratory systems was proposed as the model of the transportation system of interest. The vibration analysis of both the transportation system and the polynomial trajectories was conducted analytically to show which polynomial trajectory has the least payload vibration. A second stage of payload vibration reduction was provided by introducing a method to reduce the transmitted vibration from the quadrotor to the payload for any quadrotor trajectory. A roadmap to design the transportation task that can reduce the payload vibration was proposed. Both the simulation and the experimental results were presented, discussed and analyzed to verify the findings of this paper.

Using a variety of policy-based reinforcement learning techniques, we train a singlehidden-layer artificial neural network to balance a physically accurate simulation of a single inverted pendulum. The trained weights and biases of the neural network are then transferred to a real agent where they can be used to control and balance a real inverted pendulum, in real time. The virtually trained model is robust to sensor noise, model errors, and motor play, and is able to recover from physical disturbances to the system. We also train a radial basis function network using pilco, a model-based technique that uses Gaussian processes to propagate uncertainties through a probabilistic dynamics model to reduce model bias for long-term predictions. This technique is significantly more data-efficient, requiring an order of magnitude fewer samples than previous state-of-the art algorithms, and is better able to recover from large disturbances to the system. Its primary limitation is being significantly more computationally expensive and memory intensive. This hybrid approach of training a simulation allows thousands of trial runs to be completed orders of magnitude faster than would be possible in the real world, resulting in greatly reduced training time and more iterations, producing a more robust model.
Using a physically accurate dynamics model allows the system to overcome the sim-real gap without requiring domain randomization or a variational autoencoder to create a domain-invariant latent space. When compared with existing reinforcement learning methods, the resulting control is smoother, learned faster, and able to withstand forced disturbances.

@article{schleer_2020,
title = {Conceptual design of force reflection control for teleoperated bone surgery},
author = {Schleer, P.; Körner, D.; Vossel, M.; Drobinsky, S.; Radermacher, K.},
journal = {Current Directions in Biomedical Engineering},
year = {2020},
volume = {6},
number = {1},
institution = {Helmholtz Institute for Biomedical Engineering, Germany},
abstract = {Bilateral control of teleoperated robots still poses a challenge, especially if environment properties vary over a large degree. Most currently available systems do not provide force feedback and consequently surgeons still have to estimate contact forces predominantly visually. During drilling or milling in bone surgery, visual estimation is virtually impossible due to hardly any deformations. However, the force progression contains important complimentary information for the surgeon. Therefore, a concept for a force-reflecting controller for drilling or milling during teleoperated bone surgery was developed and tested on a one degree of freedom (DOF) test setup. First, the desired behavior and control architectures were derived based on the context of bone surgery. The resulting controller combines three control architectures in a switching controller, depending on the tool actuation and environment properties. Experimental results with a 1-DOF test setup showed the desired control and switching behavior, while remaining stable. Therefore, the developed control concept seems promising for teleoperated bone surgery. },
keywords = {bilateral control; haptics; robotic surgery},
language = {English},
publisher = {Walter de Gruyter GmbH}
}

Bilateral control of teleoperated robots still poses a challenge, especially if environment properties vary over a large degree. Most currently available systems do not provide force feedback and consequently surgeons still have to estimate contact forces predominantly visually. During drilling or milling in bone surgery, visual estimation is virtually impossible due to hardly any deformations. However, the force progression contains important complimentary information for the surgeon. Therefore, a concept for a force-reflecting controller for drilling or milling during teleoperated bone surgery was developed and tested on a one degree of freedom (DOF) test setup. First, the desired behavior and control architectures were derived based on the context of bone surgery. The resulting controller combines three control architectures in a switching controller, depending on the tool actuation and environment properties. Experimental results with a 1-DOF test setup showed the desired control and switching behavior, while remaining stable. Therefore, the developed control concept seems promising for teleoperated bone surgery.

@conference{kyeong_2020,
title = {Enhanced torque estimation method from multi-channel surface electromyography compensating electrode location variation},
author = {Kyeong, S.; Kim, J.},
booktitle = { 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)},
year = {2020},
institution = {Korea Advanced Institute of Science and Technology (KAIST)},
abstract = {Recognizing human intentions from the human counterpart is very important in human-robot interaction applications. Surface electromyography(sEMG) has been considered as a potential source for motion intention because the signal represents the on-set timing and amplitude of muscle activation. It is also reported that sEMG has the advantage of knowing body movements ahead of actual movement. However, sEMG based applications suffer from electrode location variation because sEMG shows different characteristics whenever the skin condition is different. They need to recreate the estimation model if electrodes are attached to different locations or conditions. In this paper, we developed a sEMG torque estimation model for electrode location variation. A decomposition model of sEMG signals was developed to discriminate the muscle source signals for electrode location variation, and we verified this model without making a new torque estimation model. Torque estimation accuracy using the proposed method was increased by 24.8% and torque prediction accuracy was increased by 47.7% for the electrode location variation in comparison with the method without decomposition. Therefore, the proposed sEMG decomposition method showed an enhancement in torque estimation for electrode location variation. },
issn = {1557-170X },
keywords = {Torque, Electrodes, Estimation, Force, Muscles, Predictive models, Electromyography},
language = {English},
publisher = {IEEE},
isbn = {978-1-7281-1991-5}
}

Recognizing human intentions from the human counterpart is very important in human-robot interaction applications. Surface electromyography(sEMG) has been considered as a potential source for motion intention because the signal represents the on-set timing and amplitude of muscle activation. It is also reported that sEMG has the advantage of knowing body movements ahead of actual movement. However, sEMG based applications suffer from electrode location variation because sEMG shows different characteristics whenever the skin condition is different. They need to recreate the estimation model if electrodes are attached to different locations or conditions. In this paper, we developed a sEMG torque estimation model for electrode location variation. A decomposition model of sEMG signals was developed to discriminate the muscle source signals for electrode location variation, and we verified this model without making a new torque estimation model. Torque estimation accuracy using the proposed method was increased by 24.8% and torque prediction accuracy was increased by 47.7% for the electrode location variation in comparison with the method without decomposition. Therefore, the proposed sEMG decomposition method showed an enhancement in torque estimation for electrode location variation.

The purpose of this study was to develop and evaluate a new, open-source MR-compatible device capable of assessing unipedal and bipedal lower extremity movement with minimal head motion and high test–retest reliability. To evaluate the prototype, 20 healthy adults participated in two magnetic resonance imaging (MRI) visits, separated by 2–6 months, in which they performed a visually guided dorsiflexion/plantar flexion task with their left foot, right foot, and alternating feet. Dependent measures included: evoked blood oxygen level-dependent (BOLD) signal in the motor network, head movement associated with dorsiflexion/plantar flexion, the test–retest reliability of these measurements. Left and right unipedal movement led to a significant increase in BOLD signal compared to rest in the medial portion of the right and left primary motor cortex (respectively), and the ipsilateral cerebellum (FWE corrected, p < .001). Average head motion was 0.10 ± 0.02 mm. The test–retest reliability was high for the functional MRI data (intraclass correlation coefficients [ICCs]: >0.75) and the angular displacement of the ankle joint (ICC: 0.842). This bipedal device can robustly isolate activity in the motor network during alternating plantarflexion and dorsiflexion with minimal head movement, while providing high test–retest reliability. Ultimately, these data and open-source building instructions will provide a new, economical tool for investigators interested in evaluating brain function resulting from lower extremity movement.

@conference{wiercigroch_2020,
title = {Force and torque feedback in endoscopic vessel harvesting},
author = {Wiercigroch, J.; Hashtrudi-Zaad, K.; Ungi, T.; Bisleri, G.; Fichtinger, G.},
booktitle = {Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling },
year = {2020},
institution = {Queen's University, Canada},
abstract = {PURPOSE: Endoscopic vessel harvesting is the preferred minimally invasive approach to obtain grafts for coronary bypass surgeries, however it requires extensive practice to minimize vessel damage. We propose to create a surgical training simulation with visual and haptic feedback. In this study, we focus on analyzing the force and torque peaks on the surgical retractor during the procedure. METHODS: The original retractor handle was 3D scanned and modified to attach an ATI Mini40 force-torque transducer. The forces and torques in two radial artery and two saphenous vein procedures in human cadavers were recorded. The measurements, endoscopic video and surgical surface video were collected. The median and interquartile range of the force and torque peaks were calculated for the artery and vein harvesting procedures. RESULTS: The median and interquartile range for saphenous vein harvests was larger than radial artery harvests. The largest median force and torque generated in the vein was 11.654 N [posterior] and 0.661 Nm [- frontal], whereas in the artery was 6.163 N [anterior] and 0.381 Nm [+ frontal], respectively. CONCLUSION: The distribution of force and torque peaks in the retractor was found for endoscopic vessel harvests. This data can be used to design a haptic user interface, and to establish expert benchmarks for learning curve evaluation. },
language = {English},
series = {Proceedings SPIE 11315},
publisher = {SPIE}
}

PURPOSE: Endoscopic vessel harvesting is the preferred minimally invasive approach to obtain grafts for coronary bypass surgeries, however it requires extensive practice to minimize vessel damage. We propose to create a surgical training simulation with visual and haptic feedback. In this study, we focus on analyzing the force and torque peaks on the surgical retractor during the procedure.
METHODS: The original retractor handle was 3D scanned and modified to attach an ATI Mini40 force-torque transducer. The forces and torques in two radial artery and two saphenous vein procedures in human cadavers were recorded. The measurements, endoscopic video and surgical surface video were collected. The median and interquartile range of the force and torque peaks were calculated for the artery and vein harvesting procedures.
RESULTS: The median and interquartile range for saphenous vein harvests was larger than radial artery harvests. The largest median force and torque generated in the vein was 11.654 N [posterior] and 0.661 Nm [- frontal], whereas in the artery was 6.163 N [anterior] and 0.381 Nm [+ frontal], respectively.
CONCLUSION: The distribution of force and torque peaks in the retractor was found for endoscopic vessel harvests. This data can be used to design a haptic user interface, and to establish expert benchmarks for learning curve evaluation.

@article{krupa_2020,
title = {Implementation of Model Predictive Control in Programmable Logic Controllers},
author = {krupa, P.; Limon, D.; Alamo, T.},
journal = { IEEE Transactions on Control Systems Technology},
year = {2020},
institution = {University of Seville, Spain},
abstract = {In this article, we present an implementation of a low-memory footprint model predictive control (MPC)-based controller in programmable logic controllers (PLCs). Automatic code generation of standardized IEC 61131-3 PLC programming languages is used to solve the MPC's optimization problem online. The implementation is designed for its application in a realistic industrial environment, including timing considerations and accounting for the possibility of the PLC not being exclusively dedicated to the MPC controller. We describe the controller architecture and algorithm, show the results of its memory footprint with regard to the problem dimensions, and present the results of its implementation to control a hardware-in-the-loop multivariable chemical plant. },
issn = {1063-6536 },
keywords = {Dual optimization, embedded systems, IEC 61131, model predictive control (MPC), programmable logic controller (PLC).},
language = {English},
publisher = {IEEE}
}

In this article, we present an implementation of a low-memory footprint model predictive control (MPC)-based controller in programmable logic controllers (PLCs). Automatic code generation of standardized IEC 61131-3 PLC programming languages is used to solve the MPC's optimization problem online. The implementation is designed for its application in a realistic industrial environment, including timing considerations and accounting for the possibility of the PLC not being exclusively dedicated to the MPC controller. We describe the controller architecture and algorithm, show the results of its memory footprint with regard to the problem dimensions, and present the results of its implementation to control a hardware-in-the-loop multivariable chemical plant.

@article{shen_2020,
title = {Improving Tracking Performance of Nonlinear Uncertain Bilateral Teleoperation Systems with Time-Varying Delays and Disturbances},
author = {Shen, H.; Pan, Y.-J.},
journal = {IEEE/ASME Transactions on Mechatronics},
year = {2020},
institution = { Dalhousie University, Canada},
abstract = {In this paper, an adaptive non-singular terminal sliding mode (ANTSM) method is proposed for the motion tracking control of a bilateral teleoperation system. Efforts in this paper seek to improve the position tracking performance of nonlinear systems subject to time-varying network delays, parametric uncertainties, and unknown external disturbances and frictions. Another issue addressed in this paper is the common delay-induced phase shift of tracking profiles in many control methods, which is greatly reduced by introducing a novel mixed-type of feedback signals in the ANTSM control design. Furthermore, the proposed adaptive control design with two online-estimated compensatory bounds removes the requirement of exact knowledge of network delays and disturbance bounds as a prior. In the master side, a force predictor is used to estimate the current environmental force for the reference signal generator. Therefore, the direct transmission of force signals is avoided. By comparing with the existing model-based and model-free methods, numerical simulation results with six degrees of freedom (6 DOFs) manipulators illustrate the merits of the developed robust and adaptive controllers. Experimental results with two Phantom Omni devices are also provided to demonstrate the effectiveness and the significant performance improvements of the proposed controllers. },
issn = {1941-014X },
keywords = {Nonlinear Bilateral Teleoperation, Non-Singular Terminal Sliding Mode, Adaptive Control, Time-Varying Network Delays, Phase Shift, Mixed-Type Feedback},
language = {English},
publisher = {IEEE}
}

In this paper, an adaptive non-singular terminal sliding mode (ANTSM) method is proposed for the motion tracking control of a bilateral teleoperation system. Efforts in this paper seek to improve the position tracking performance of nonlinear systems subject to time-varying network delays, parametric uncertainties, and unknown external disturbances and frictions. Another issue addressed in this paper is the common delay-induced phase shift of tracking profiles in many control methods, which is greatly reduced by introducing a novel mixed-type of feedback signals in the ANTSM control design. Furthermore, the proposed adaptive control design with two online-estimated compensatory bounds removes the requirement of exact knowledge of network delays and disturbance bounds as a prior. In the master side, a force predictor is used to estimate the current environmental force for the reference signal generator. Therefore, the direct transmission of force signals is avoided. By comparing with the existing model-based and model-free methods, numerical simulation results with six degrees of freedom (6 DOFs) manipulators illustrate the merits of the developed robust and adaptive controllers. Experimental results with two Phantom Omni devices are also provided to demonstrate the effectiveness and the significant performance improvements of the proposed controllers.

Teleoperation of multiple robot manipulators has been one of the most popular research areas in the robotics research community for the last couple of decades. Such complex systems can be decoupled into two subsystems, namely, multi-agent systems (MASs) and teleoperation systems. In addition to the high nonlinearity of the networked multi-manipulator systems, deleterious effects, caused by network-induced constraints and the lack of exact robot modelling information, can make the control systems’ desired performance and stability difficult to achieve. To meet these challenges, concepts from the non-singular terminal sliding mode (NTSM) control method are developed to achieve the exogenous disturbance rejection and the finite-time full-pose synchronization. Additionally, a new adaptive NTSM (ANTSM) scheme is designed for multi-manipulator systems where the models may be initially uncertain or slowly varying over time. To further improve the performance, a set of novel techniques are developed, including the use of novel mixed-type feedback, time-varying logistic-function-based control gain, and energy-index-based neighbour selection policy. The proposed ANTSM approach has also successfully been applied to the teleoperation control systems. In addition, the master manipulator uses a force predictor to estimate the real-time environmental force on the slave side so that the direct transmission of the force signals is avoided. The proposed approaches for the MASs and teleoperation subsystems are integrated into a single-master-multiple-slave manipulator system. Simulation and experimental results validate the efficacy of the proposed schemes.

@conference{dogan2_2020,
title = {Performance Guarantees in Adaptive Control of Uncertain Systems with Unmodeled Dynamics},
author = {Dogan, K.M.; Yucelen, T.; Muse, J.A.},
booktitle = {AIAA Scitech 2020 Forum},
year = {2020},
institution = {University of South Florida, USA},
abstract = {The presence of unmodeled dynamics degrades the stability and performance of adaptive control architectures. While there are studies that focus on the stability aspects of adaptive control architectures for uncertain systems with unmodeled dynamics, methods that offer performance guarantees in the sense of predictably minimizing the difference between uncertain system trajectories and given reference model trajectories are not available in the literature. In this paper, we address this gap through a recently developed direct uncertainty minimization framework. Specifically, a model reference adaptive control architecture is proposed and mathematically analyzed for uncertain systems with unmodeled dynamics. The key feature of our architecture is the added term in the control signal and the update law, which is developed through a gradient descent procedure with a new cost function involving a cost function gain in order to minimize the effect of both system uncertainties and unmodeled dynamics on the closed-loop system response. Therefore, the proposed architecture can be effective in achieving performance guarantees, where an illustrative numerical example shows the offered predictable performance as a function of the cost function gain. Finally, we also provide an experimental study on a physical system involving two carts connected with each other through a spring in order to demonstrate the efficacy of the proposed architecture. },
language = {English},
publisher = {AIAA}
}

The presence of unmodeled dynamics degrades the stability and performance of adaptive control architectures. While there are studies that focus on the stability aspects of adaptive control architectures for uncertain systems with unmodeled dynamics, methods that offer performance guarantees in the sense of predictably minimizing the difference between uncertain system trajectories and given reference model trajectories are not available in the literature. In this paper, we address this gap through a recently developed direct uncertainty minimization framework. Specifically, a model reference adaptive control architecture is proposed and mathematically analyzed for uncertain systems with unmodeled dynamics. The key feature of our architecture is the added term in the control signal and the update law, which is developed through a gradient descent procedure with a new cost function involving a cost function gain in order to minimize the effect of both system uncertainties and unmodeled dynamics on the closed-loop system response. Therefore, the proposed architecture can be effective in achieving performance guarantees, where an illustrative numerical example shows the offered predictable performance as a function of the cost function gain. Finally, we also provide an experimental study on a physical system involving two carts connected with each other through a spring in order to demonstrate the efficacy of the proposed architecture.

@conference{islam_2020,
title = {Position-Velocity/Position Based Robust Control for Shared Autonomous System Over Open Communication Networks-Experimental Results},
author = {Islam, S.},
booktitle = {2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)},
year = {2020},
institution = {Xavier University of Louisiana, USA},
abstract = {This paper experimentally compares position-velocity/position and interaction reflection based bilateral shared control telemanipulation system over open internet networks with the presence of delay and uncertainty. The shared control algorithm for master and slave manipulator is designed by using two classes of signals: delayed position and position-velocity. The shared control for the master manipulator is developed by comprising the delayed position-velocity and position of the slave with the delayed interaction reflection from the interaction between slave and remote environment. The shared control for slave manipulator is developed by using delayed position-velocity and position of the master manipulator. Robust adaptation learning laws are employed locally with the input of the master and slave manipulator to estimate the interaction properties between human and master manipulator and between slave and remote environment. The delayed estimated interaction between slave and remote environment reflects to the operators hand in order to adjust with the estimated interaction properties between master and human operator. Robust and adaptive control theory used to learn and compensate uncertainty associated with the modeling errors and other external disturbance. Lyapunov method is used to show the convergence of the closed loop system with the presence of time varying delay and uncertainty. The test results are presented to compare the effectiveness of the position-velocity and position based robust control interface for real-time bilateral telemanipulation applications. },
issn = {2159-6247 },
keywords = {Delays, Uncertainty, Robustness, Force, Manipulator dynamics, Convergence},
language = {English},
publisher = {IEEE},
isbn = {978-1-7281-6795-4}
}

This paper experimentally compares position-velocity/position and interaction reflection based bilateral shared control telemanipulation system over open internet networks with the presence of delay and uncertainty. The shared control algorithm for master and slave manipulator is designed by using two classes of signals: delayed position and position-velocity. The shared control for the master manipulator is developed by comprising the delayed position-velocity and position of the slave with the delayed interaction reflection from the interaction between slave and remote environment. The shared control for slave manipulator is developed by using delayed position-velocity and position of the master manipulator. Robust adaptation learning laws are employed locally with the input of the master and slave manipulator to estimate the interaction properties between human and master manipulator and between slave and remote environment. The delayed estimated interaction between slave and remote environment reflects to the operators hand in order to adjust with the estimated interaction properties between master and human operator. Robust and adaptive control theory used to learn and compensate uncertainty associated with the modeling errors and other external disturbance. Lyapunov method is used to show the convergence of the closed loop system with the presence of time varying delay and uncertainty. The test results are presented to compare the effectiveness of the position-velocity and position based robust control interface for real-time bilateral telemanipulation applications.

@conference{singhala_2020,
title = {Prefatory study of the effects of exploration dynamics on stiffness perception},
author = {Singhala, M.; Brown, J.D.},
booktitle = {2020 IEEE Haptics Symposium},
year = {2020},
institution = {Johns Hopkins University, USA},
abstract = {The utility of telerobotic systems is driven in large part by the quality of feedback they provide to the operator. While the dynamic interaction between a robot and the environment can often be sensed or modeled, the dynamic coupling at the human-robot interface is often overlooked. Improving dexterous manipulation through telerobots will require careful consideration of human haptic perception as it relates to human exploration dynamics at the telerobotic interface. In this manuscript, we use exploration velocity as a means of controlling the operator’s exploration dynamics, and present results from two stiffness discrimination experiments designed to investigate the effects of exploration velocity on stiffness perception. The results indicate that stiffness percepts vary differently for different exploration velocities on an individual level, however, no consistent trends were found across all participants. These results suggest that exploration dynamics can affect the quality of haptic interactions through telerobotic interfaces, and also reflect the need to study the underlying mechanisms that cause our perception to vary with our choice of exploration strategy. },
issn = {2324-7347 },
language = {English},
publisher = {IEEE}
}

The utility of telerobotic systems is driven in large part by the quality of feedback they provide to the operator. While the dynamic interaction between a robot and the environment can often be sensed or modeled, the dynamic coupling at the human-robot interface is often overlooked. Improving dexterous manipulation through telerobots will require careful consideration of human haptic perception as it relates to human exploration dynamics at the telerobotic interface. In this manuscript, we use exploration velocity as a means of controlling the operator’s exploration dynamics, and present results from two stiffness discrimination experiments designed to investigate the effects of exploration velocity on stiffness perception. The results indicate that stiffness percepts vary differently for different exploration velocities on an individual level, however, no consistent trends were found across all participants. These results suggest that exploration dynamics can affect the quality of haptic interactions through telerobotic interfaces, and also reflect the need to study the underlying mechanisms that cause our perception to vary with our choice of exploration strategy.

@conference{tigue_2020,
title = {Simulating Tendon Shortening During Flexor Tendon Repair Surgery Using A Biomechanical Model and Robotic Testbed},
author = {Tigue, J.A.; Bradford Rockwell, W.; Bo Foreman, K.; Mascaro, S.},
booktitle = {2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)},
year = {2020},
institution = {University of Utah, USA},
abstract = {Current reconstructive hand tendon surgeries are based on clinical experience and cadaver studies. New biomechanical hand models and anatomically correct robotic testbeds provide a potential alternative to surgical trial-and error or cumbersome cadaver studies. We introduce a new index finger biomechanical model and anatomically correct robotic testbed to explore this potential application. The model and testbed are used in developing a novel methodology for simulating the active range of motion outcomes of flexor digitorum profundus repair surgery based on shortening of the tendon that can occur during reconstruction. Simulated and experimental results demonstrate the benefits of using both models and robotic testbeds. Results also support the clinical recommendation of a 10 mm shortening limiting to maintain functionality. },
issn = {2155-1774},
language = {English},
publisher = {IEEE}
}

Current reconstructive hand tendon surgeries are based on clinical experience and cadaver studies. New biomechanical hand models and anatomically correct robotic testbeds provide a potential alternative to surgical trial-and error or cumbersome cadaver studies. We introduce a new index finger biomechanical model and anatomically correct robotic testbed to explore this potential application. The model and testbed are used in developing a novel methodology for simulating the active range of motion outcomes of flexor digitorum profundus repair surgery based on shortening of the tendon that can occur during reconstruction. Simulated and experimental results demonstrate the benefits of using both models and robotic testbeds. Results also support the clinical recommendation of a 10 mm shortening limiting to maintain functionality.

@article{duenas_2020,
title = {Torque and cadence tracking in functional electrical stimulation induced cycling using passivity-based spatial repetitive learning control},
author = {Duenas, V.H.; Cousin, C.A.; Ghanbari, V.; Fox, E.J.; Dixon, W.E.},
journal = {Automatica},
year = {2020},
month = {05},
volume = {115},
institution = {Syracuse University, USA; University of Alabama, USA; University of Notre Dame, USA; University of Florida, USA},
abstract = {Due to the inherent periodic nature of cycling tasks, iterative and repetitive learning controllers are well motivated for rehabilitative cycling. Motorized functional electrical stimulation induced cycling is a rehabilitation treatment where multiple lower-limb muscle groups are activated jointly with an electric motor to achieve cycling objectives such as speed (cadence) and torque tracking. This paper examines torque tracking accomplished by the stimulation of six lower-limb muscles via a novel spatial repetitive learning control and cadence regulation by an electric motor using a sliding-mode controller. A desired torque trajectory is constructed based on the rider’s kinematic efficiency, which is a function of the crank position. The learning controller takes advantage of the periodicity of the desired torque trajectory to provide a feedforward input to the stimulated muscles. A passivity-based analysis is developed to ensure stability of the torque and cadence closed-loop error systems. The muscle learning and electric motor controllers were implemented in real-time during cycling experiments on five able-bodied individuals and three participants with movement disorders. The combined average cadence tracking error was RPM for a 50 RPM trajectory and the combined average power tracking error was W for a peak power of 10 W. },
keywords = {Functional Electrical Stimulation (FES), FES-cycling, Spatial repetitive learning control (RLC), Passivity-based control H,uman–machine interaction},
language = {English},
publisher = {Elsevier Ltd.}
}

Due to the inherent periodic nature of cycling tasks, iterative and repetitive learning controllers are well motivated for rehabilitative cycling. Motorized functional electrical stimulation induced cycling is a rehabilitation treatment where multiple lower-limb muscle groups are activated jointly with an electric motor to achieve cycling objectives such as speed (cadence) and torque tracking. This paper examines torque tracking accomplished by the stimulation of six lower-limb muscles via a novel spatial repetitive learning control and cadence regulation by an electric motor using a sliding-mode controller. A desired torque trajectory is constructed based on the rider’s kinematic efficiency, which is a function of the crank position. The learning controller takes advantage of the periodicity of the desired torque trajectory to provide a feedforward input to the stimulated muscles. A passivity-based analysis is developed to ensure stability of the torque and cadence closed-loop error systems. The muscle learning and electric motor controllers were implemented in real-time during cycling experiments on five able-bodied individuals and three participants with movement disorders. The combined average cadence tracking error was RPM for a 50 RPM trajectory and the combined average power tracking error was W for a peak power of 10 W.

@article{shen3_2020,
title = {Tracking Synchronization Improvement of Networked Manipulators Using Novel Adaptive Non-Singular Terminal Sliding Mode Control},
author = {Shen, H.; Pan, Y.-J.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2020},
institution = {Dalhousie University, Canada},
abstract = {In this paper we focus on the experimental validation of the developed adaptive non-singular terminal sliding mode (ANTSM) controller for a networked manipulator system. The proposed control approach is designed to deal with a combination of adverse and inexactly known conditions in practice, including parametric uncertainties, frictions, exogenous disturbances, and random time-varying network delays. Another issue addressed in this paper is the trade-off between achieving a smooth convergence and a high tracking accuracy in the physical implementation of the ANTSM controller. Hence a novel time-varying gain in a form of logistic function is introduced to provide converging smoothness and meanwhile improve the tracking accuracy. Experimental results and empirical analysis are provided to demonstrate the effectiveness and performance improvement of the proposed controller with a time-varying gain. },
issn = {0278-0046 },
keywords = {Adaptive Control, Networked Control Systems, Non-Singular Terminal Sliding Mode (NTSM), Time-Varying Gain},
language = {English},
publisher = {IEEE}
}

In this paper we focus on the experimental validation of the developed adaptive non-singular terminal sliding mode (ANTSM) controller for a networked manipulator system. The proposed control approach is designed to deal with a combination of adverse and inexactly known conditions in practice, including parametric uncertainties, frictions, exogenous disturbances, and random time-varying network delays. Another issue addressed in this paper is the trade-off between achieving a smooth convergence and a high tracking accuracy in the physical implementation of the ANTSM controller. Hence a novel time-varying gain in a form of logistic function is introduced to provide converging smoothness and meanwhile improve the tracking accuracy. Experimental results and empirical analysis are provided to demonstrate the effectiveness and performance improvement of the proposed controller with a time-varying gain.

Cooperative surgical systems enable humans and machines to combine their individual strengths and collaborate to improve the surgical outcome. Cooperative telemanipulated systems offer the widest spectrum of cooperative functionalities, because motion scaling is possible. Haptic guidance can be used to assist surgeons and haptic feedback makes acting forces at the slave side transparent to the operator, however, overlapping and masking of forces needs to be avoided. This study evaluates the usability of a cooperative surgical telemanipulator in a laboratory setting.

@article{butt_2019,
title = {A Nonlinear Integral Sliding Surface to Improve the Transient Response of a Force-Controlled Pneumatic Actuator With Long Transmission Lines},
author = {Butt, K.; Sepehri, N.},
journal = {Journal of Dynamic Systems, Measurement, and Control},
year = {2019},
month = {12},
volume = {141},
number = {12},
institution = {University of Manitoba, Canada},
abstract = {A force-controlled pneumatic actuator with long connecting tubes is a well-accepted solution to develop magnetic resonance imaging (MRI)-compatible force control applications. Such an actuator represents an uncertain, second-order, nonlinear system with input delay. The integral sliding mode control, because of guaranteed robustness against matched uncertainties throughout the system response, provides a favorable option to design a robust controller for the actuator. However, if the controller is based on a linear integral sliding surface (LISS), the response of the actuator overshoots, especially when there are large initial errors. Minimizing overshoot results in a smaller controller bandwidth and a slower system response. This paper presents a novel nonlinear integral sliding surface (NLISS) for a sliding mode controller to improve the transient response of the actuator. The proposed surface is a LISS augmented by a nonlinear function of tracking error and does not have a reaching phase when there are initial errors and even multiple steps in the desired trajectory. The surface enables the integral sliding mode controller to offer variable damping, which changes from low to high as the transient error approaches small values and vice versa. Simulation studies and experimental results show that the controller based on the proposed sliding surface successfully eliminates the overshoot without compromising the controller bandwidth, rise, and settling times. For performance evaluation, the controller parameters are tuned using the globalized and bounded Nelder–Mead (GBNM) algorithm with deterministic restarts. The study also establishes the asymptotic stability of the controller based on the proposed sliding surface using Lyapunov's stability criterion. },
keywords = {force control, pneumatic actuator, input delay, integral sliding mode control, nonlinear integral sliding surface},
language = {English},
publisher = {ASME}
}

A force-controlled pneumatic actuator with long connecting tubes is a well-accepted solution to develop magnetic resonance imaging (MRI)-compatible force control applications. Such an actuator represents an uncertain, second-order, nonlinear system with input delay. The integral sliding mode control, because of guaranteed robustness against matched uncertainties throughout the system response, provides a favorable option to design a robust controller for the actuator. However, if the controller is based on a linear integral sliding surface (LISS), the response of the actuator overshoots, especially when there are large initial errors. Minimizing overshoot results in a smaller controller bandwidth and a slower system response. This paper presents a novel nonlinear integral sliding surface (NLISS) for a sliding mode controller to improve the transient response of the actuator. The proposed surface is a LISS augmented by a nonlinear function of tracking error and does not have a reaching phase when there are initial errors and even multiple steps in the desired trajectory. The surface enables the integral sliding mode controller to offer variable damping, which changes from low to high as the transient error approaches small values and vice versa. Simulation studies and experimental results show that the controller based on the proposed sliding surface successfully eliminates the overshoot without compromising the controller bandwidth, rise, and settling times. For performance evaluation, the controller parameters are tuned using the globalized and bounded Nelder–Mead (GBNM) algorithm with deterministic restarts. The study also establishes the asymptotic stability of the controller based on the proposed sliding surface using Lyapunov's stability criterion.

@article{niu_2019,
title = {Adaptive phase compensator for vibration suppression of structures with parameter perturbation},
author = {Niu, W.; Li, B.},
journal = {Aerospace Science and Technology},
year = {2019},
institution = {Northwestern Polytechnical University, China},
abstract = {The constant all-pass filter has been widely used for phase compensation of control systems. However, it is not applicable to compensating phase deviation caused by additional filters to enhance the signal quality in vibration control systems with parameter perturbation. To overcome this challenge, an adaptive phase compensator (APC) is developed by transforming the constant parameters of an all-pass filter into frequency-dependent parameters. In addition, the sources of phase deviations in the control system are analyzed to design the APC, including the additional filters, non-collocated actuator/sensor configuration, and hardware hysteresis. The phase deviations are determined through simulation and experiment. Polynomial fitting is implemented to obtain the APC parameters. To verify the feasibility of the proposed APC, numerical and experimental efforts are undertaken for buffeting suppression of the vertical tail, which is a typical structure with parameter perturbation. Both results demonstrate that the stability and robustness of control system adopting APC are strengthened compared to that of the control system using a constant phase compensator. Moreover, a control system that adopts APC can also effectively reduce the vibration response for structures with parameter perturbation under harmonic and random excitations. This performance improvement indicates that the proposed APC provides more effective compensation performance for the phase deviation of control systems with time-varying perturbations. },
keywords = {Adaptive phase compensator, Phase compensation for additional filter, Estimation of phase deviation, Structure with parameter perturbation, Vibration control of vertical tail},
language = {English},
publisher = {Elsevier Masson SAS}
}

The constant all-pass filter has been widely used for phase compensation of control systems. However, it is not applicable to compensating phase deviation caused by additional filters to enhance the signal quality in vibration control systems with parameter perturbation. To overcome this challenge, an adaptive phase compensator (APC) is developed by transforming the constant parameters of an all-pass filter into frequency-dependent parameters. In addition, the sources of phase deviations in the control system are analyzed to design the APC, including the additional filters, non-collocated actuator/sensor configuration, and hardware hysteresis. The phase deviations are determined through simulation and experiment. Polynomial fitting is implemented to obtain the APC parameters. To verify the feasibility of the proposed APC, numerical and experimental efforts are undertaken for buffeting suppression of the vertical tail, which is a typical structure with parameter perturbation. Both results demonstrate that the stability and robustness of control system adopting APC are strengthened compared to that of the control system using a constant phase compensator. Moreover, a control system that adopts APC can also effectively reduce the vibration response for structures with parameter perturbation under harmonic and random excitations. This performance improvement indicates that the proposed APC provides more effective compensation performance for the phase deviation of control systems with time-varying perturbations.

@article{niu_2018,
title = {Adaptive vibration suppression of time-varying structures with enhanced FxLMS algorithm},
author = {Niu, W.; Zou, C.; Li, B.; Wanga, W.},
journal = {Mechanical Systems and Signal Processing},
year = {2019},
month = {03},
volume = {118},
institution = {Northwestern Polytechnical University, China; Ohio State University, USA},
abstract = {Filtered-x least mean square (FxLMS) control algorithm has been widely used for adaptive noise and vibration control. Yet, classical FxLMS controller is not applicable for time-varying system since the secondary path identified offline cannot reflect the system characteristics in real-time. In order to overcome this challenge, here online modelling of secondary path is realized by existing signals, i.e. no noise injection. In addition, FxLMS is further enhanced with variable step size that is adaptively adjusted via bang-bang controller. The adaptation of step size is aimed to achieve the balance between control efficiency and system stability. To verify the feasibility of proposed control algorithm, numerical and experimental efforts are undertaken for the buffeting suppression of vertical tail which is a typical time-varying system. Both results demonstrate that the proposed method is able to reduce the vibration response effectively for varied structures under harmonic and random excitations, while the classical FxLMS cannot. This performance improvement indicates that the online modeling of secondary path captures the system characteristics accurately and timely. Moreover, compared with the FxLMS controller with fixed step size, the control efficiency of the proposed method is also strengthened. These multiple enhancements of the performance of FxLMS controller reveal that online modeling and variable step size are favorable for adaptive vibration control of time-varying structures. },
keywords = {Filtered-x least mean square, Bang-bang control, Variable step size, Online identification, Time-varying structures},
language = {English},
publisher = {Elsevier Ltd.}
}

Filtered-x least mean square (FxLMS) control algorithm has been widely used for adaptive noise and vibration control. Yet, classical FxLMS controller is not applicable for time-varying system since the secondary path identified offline cannot reflect the system characteristics in real-time. In order to overcome this challenge, here online modelling of secondary path is realized by existing signals, i.e. no noise injection. In addition, FxLMS is further enhanced with variable step size that is adaptively adjusted via bang-bang controller. The adaptation of step size is aimed to achieve the balance between control efficiency and system stability. To verify the feasibility of proposed control algorithm, numerical and experimental efforts are undertaken for the buffeting suppression of vertical tail which is a typical time-varying system. Both results demonstrate that the proposed method is able to reduce the vibration response effectively for varied structures under harmonic and random excitations, while the classical FxLMS cannot. This performance improvement indicates that the online modeling of secondary path captures the system characteristics accurately and timely. Moreover, compared with the FxLMS controller with fixed step size, the control efficiency of the proposed method is also strengthened. These multiple enhancements of the performance of FxLMS controller reveal that online modeling and variable step size are favorable for adaptive vibration control of time-varying structures.

@article{cao_2019,
title = {ADRC-Based Current Control for Grid-Tied Inverters: Design, Analysis, and Verification},
author = {Cao, Y.; Zhao, Q.; Ye, Y.; Xiong, Y.},
journal = { IEEE Transactions on Industrial Electronics},
year = {2019},
institution = {Nanjing University of Aeronautics and Astronautics, China},
abstract = {The conversion and utilisation of renewable energy generations often require grid-tied inverters. When an LCL filter is applied to attenuate the high switching frequency harmonics, it is complex to design a controller with proper parameters due to the characteristics of the LCL filter and system uncertainties. In this paper, with LCCL filter, the order of the inverter system is degraded from third-order to first-order, and an ADRC-based current control strategy for LCCL-type grid-tied inverters is proposed. The proposed strategy is able to treat the unknown dynamics and the external disturbance of the inverter system as overall disturbance through a single structure, and the closedloop system is regulated by an improved control law with reference differential feedforward. Moreover, with parameter uncertainties considered, the robustness of the proposed strategy is studied through an internal model control structure. A 2-kW experimental prototype has been tested to verify the effectiveness of the proposed scheme. },
issn = {0278-0046},
keywords = {Active disturbance rejection control (ADRC), LCCL filter, inverter, current control, internal model control (IMC) structure},
language = {English},
publisher = {IEEE}
}

The conversion and utilisation of renewable energy generations often require grid-tied inverters. When an LCL filter is applied to attenuate the high switching frequency harmonics, it is complex to design a controller with proper parameters due to the characteristics of the LCL filter and system uncertainties. In this paper, with LCCL filter, the order of the inverter system is degraded from third-order to first-order, and an ADRC-based current control strategy for LCCL-type grid-tied inverters is proposed. The proposed strategy is able to treat the unknown dynamics and the external disturbance of the inverter system as overall disturbance through a single structure, and the closedloop system is regulated by an improved control law with reference differential feedforward. Moreover, with parameter uncertainties considered, the robustness of the proposed strategy is studied through an internal model control structure. A 2-kW experimental prototype has been tested to verify the effectiveness of the proposed scheme.

Functional electrical stimulation (FES) has proven to be an effective method for improving health and regaining muscle function for people with limited or reduced motor skills. Closed-loop control of motorized FES-cycling can facilitate recovery. Many people with movement disorders (e.g., stroke) have asymmetries in their motor control, motivating the need for a closed-loop control system that can be implemented on a split-crank cycle. In this paper, nonlinear sliding mode controllers are designed for the FES and electric motor on each side of a split-crank cycle to maintain a desired cadence and a crank angle offset of 180 degrees, simulating standard pedaling conditions. A Lyapunov-like function is used to prove stability and tracking of the desired cadence and position for the combined cycle-rider system. One experimental trial on an able-bodied individual demonstrated the feasibility and stability of the closed-loop controller, which resulted in an average cadence error of 2:62 ± 3:54 RPM for the dominant leg and an average position and cadence error of 39:84 ± 10:77 degrees and -0:04 ± 8:79 RPM for the non-dominant leg.

@article{dong_20198,
title = {Decentralized robust zero-sum neuro-optimal control for modular robot manipulators in contact with uncertain environments: theory and experimental verification},
author = {Dong, B.; An, T.; Zhou, F.; Liu; K.; Li, Y.},
journal = {Nonlinear Dynamics},
year = {2019},
institution = {Changchun University of Technology, China},
abstract = {This paper presents a decentralized robust zero-sum optimal control approach for modular robot manipulators (MRMs) in contact with uncertain environments based on the adaptive dynamic programming (ADP) algorithm. The dynamic model of MRMs is formulated via joint torque feedback technique that is deployed for each joint module to design the model compensation controller. An uncertainty decomposition-based robust control is developed to compensate the model uncertainties, and then, the robust optimal control problem of the MRM system is transformed into a two-player zero-sum optimal control one. According to the ADP algorithm, the Hamilton–Jacobi–Isaacs equation can be solved by establishing action and critic neural networks, thus making the derivation of the approximate optimal control policy feasible. Based on the Lyapunov theory, the closed-loop robotic system is proved to be asymptotic stable under the developed decentralized control method. Finally, experiments are conducted to verify the effectiveness and advantages of the proposed method. },
issn = {0924-090X},
keywords = {Modular robot manipulators, Adaptive dynamic programming, Decentralized control, Optimal control, Zero-sum game },
language = {English},
publisher = {Springer Netherlands}
}

This paper presents a decentralized robust zero-sum optimal control approach for modular robot manipulators (MRMs) in contact with uncertain environments based on the adaptive dynamic programming (ADP) algorithm. The dynamic model of MRMs is formulated via joint torque feedback technique that is deployed for each joint module to design the model compensation controller. An uncertainty decomposition-based robust control is developed to compensate the model uncertainties, and then, the robust optimal control problem of the MRM system is transformed into a two-player zero-sum optimal control one. According to the ADP algorithm, the Hamilton–Jacobi–Isaacs equation can be solved by establishing action and critic neural networks, thus making the derivation of the approximate optimal control policy feasible. Based on the Lyapunov theory, the closed-loop robotic system is proved to be asymptotic stable under the developed decentralized control method. Finally, experiments are conducted to verify the effectiveness and advantages of the proposed method.

@article{li3_2019,
title = {Deep learning for haptic feedback of flexible endoscopic robot without prior knowledge on sheath configuration},
author = {Li, X.; Tiong, A.M.H.; Cao, L.; Lai, W.; Phan, P.T.; Phee, S.J.},
journal = {International Journal of Mechanical Sciences},
year = {2019},
month = {11},
volume = {163},
institution = {Nanyang Technological University, Singapore},
abstract = {Distal-end force information is usually missing in flexible endoscopic robots due to the difficulties of mounting miniature force sensors on their end-effectors. This hurdle creates big challenges in providing a sense of touch for the operating surgeons. Many existing studies have developed models to calculate the distal-end forces based on the measured proximal-end forces of Tendon-Sheath Mechanisms (TSMs), but these models assume known sheath bending configuration which is unknown during real-life surgeries. This paper presents a two-stage data-driven method that makes dynamic distal-end force prediction of a flexible endoscopic robot without this assumption. In stage one, a convolutional neural network is used to estimate the sheath cumulative bending angle based on the proximal-end force responses of the robot to a probing signal; in stage two, a combination of two long-short-term-memory models pre-trained for the bending angles nearest to the estimated angle (obtained in stage one) makes dynamic estimations of the distal-end force of the robot. The proposed approach overcomes the challenges due to unknown TSM configurations and can robustly identify the correct force hysteresis phases of TSMs. The force prediction is continuous, accurate, and has a mean RMSE of 0.1711 N. This method was validated on an actual flexible surgical robot. In addition, since the proposed approach provides an estimation of the current system cumulative bending angle, it can also be used to facilitate the mathematical modeling methods which require information on the cumulative bending angle. },
keywords = {Flexible endoscopic surgical robots, Tendon-sheath mechanisms, Haptic Force Feedback, Force Hysteresis, Deep Learning},
language = {English},
publisher = {Elsevier Ltd.}
}

Distal-end force information is usually missing in flexible endoscopic robots due to the difficulties of mounting miniature force sensors on their end-effectors. This hurdle creates big challenges in providing a sense of touch for the operating surgeons. Many existing studies have developed models to calculate the distal-end forces based on the measured proximal-end forces of Tendon-Sheath Mechanisms (TSMs), but these models assume known sheath bending configuration which is unknown during real-life surgeries. This paper presents a two-stage data-driven method that makes dynamic distal-end force prediction of a flexible endoscopic robot without this assumption. In stage one, a convolutional neural network is used to estimate the sheath cumulative bending angle based on the proximal-end force responses of the robot to a probing signal; in stage two, a combination of two long-short-term-memory models pre-trained for the bending angles nearest to the estimated angle (obtained in stage one) makes dynamic estimations of the distal-end force of the robot. The proposed approach overcomes the challenges due to unknown TSM configurations and can robustly identify the correct force hysteresis phases of TSMs. The force prediction is continuous, accurate, and has a mean RMSE of 0.1711 N. This method was validated on an actual flexible surgical robot. In addition, since the proposed approach provides an estimation of the current system cumulative bending angle, it can also be used to facilitate the mathematical modeling methods which require information on the cumulative bending angle.

@conference{mehrabi_2019,
title = {Design and Implementation of a Two-DOF Robotic System with an Adjustable Force Limiting Mechanism for Ankle Rehabilitation},
author = {Mehrabi, V.; Atashzar, S.F.; Talebi, H.A.; Patel, R.V.},
booktitle = {2019 International Conference on Robotics and Automation (ICRA)},
year = {2019},
institution = {Western University, Canada; Imperial College London, U.K.},
abstract = {This paper presents a novel light-weight backdrivable inherently-safe robotic mechanism for delivering ankle rehabilitation therapies. The robot is designed to be used as the ankle module of a multi-purpose lower-limb rehabilitation robot. A novel friction-based safety feature has been introduced that enables mechanical adjustment of the maximum amount of allowable transfer forces and torques to the patient’s limb. The design procedure, mathematical modeling and experimental validations are provided to demonstrate the performance of the proposed system. },
language = {English},
publisher = {IEEE}
}

This paper presents a novel light-weight backdrivable inherently-safe robotic mechanism for delivering ankle rehabilitation therapies. The robot is designed to be used as the ankle module of a multi-purpose lower-limb rehabilitation robot. A novel friction-based safety feature has been introduced that enables mechanical adjustment of the maximum amount of allowable transfer forces and torques to the patient’s limb. The design procedure, mathematical modeling and experimental validations are provided to demonstrate the performance of the proposed system.

@article{wu_2019,
title = {Discrete-Time Modified UDE-Based Current Control for LCL-Type Grid-Tied Inverters},
author = {Wu, Y.; Ye, Y.; Zhao, Q.; Cao, Y.; Xiong, Y.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2019},
institution = {Zhongyuan University of Technology, China; Nanjing University of Aeronautics and Astronautics, China},
abstract = { In LCL-type grid tied inverters, the lumped disturbance, including parameter uncertainties, unmodeled dynamics, grid harmonics, will deteriorate the current tracking performance and lead to high total harmonic distortion (THD). The uncertainty and disturbance estimator (UDE) scheme provides an effective way to attenuate the lumped disturbance. However, UDE for the current control in LCL-type grid-tied inverters is far from perfection. In this paper, a discrete-time modified UDE (MUDE) scheme is proposed to improve the current tracking performance and robustness. In MUDE, a reduced-order model of the LCL filter combining with an active damping scheme is proposed. The stability performance is discussed in detail, and a rigorous stability condition is proposed in the first time. Moreover, the analysis of the controller sampling frequency and grid impedance, and their influences on the system stability is presented. A design case based on the stability condition is also given. Comparative experiments are conducted to verify the effectiveness of the proposed scheme. },
issn = {0278-0046 },
keywords = {Grid-tied inverter, LCL filter, uncertainty and disturbance estimator (UDE), stability analysis, total harmonic distortion (THD)},
language = {English},
publisher = {IEEE}
}

In LCL-type grid tied inverters, the lumped disturbance, including parameter uncertainties, unmodeled dynamics, grid harmonics, will deteriorate the current tracking performance and lead to high total harmonic distortion (THD). The uncertainty and disturbance estimator (UDE) scheme provides an effective way to attenuate the lumped disturbance. However, UDE for the current control in LCL-type grid-tied inverters is far from perfection. In this paper, a discrete-time modified UDE (MUDE) scheme is proposed to improve the current tracking performance and robustness. In MUDE, a reduced-order model of the LCL filter combining with an active damping scheme is proposed. The stability performance is discussed in detail, and a rigorous stability condition is proposed in the first time. Moreover, the analysis of the controller sampling frequency and grid impedance, and their influences on the system stability is presented. A design case based on the stability condition is also given. Comparative experiments are conducted to verify the effectiveness of the proposed scheme.

@article{li_2019,
title = {Distal-end force prediction of tendon-sheath mechanisms for flexible endoscopic surgical robots using deep learning},
author = {Li, X.; Cao, L.; Huat Tiong, A.M.; Phan, P.T.; Phee, S.J.},
journal = {Mechanism and Machine Theory},
year = {2019},
month = {04},
volume = {134},
institution = {Nanyang Technological University, Singapore},
abstract = {Accurate haptic feedback is highly challenging for flexible endoscopic surgical robots due to space limitation for sensors on small end-effectors and critical force hysteresis of their tendon-sheath mechanisms (TSMs). This paper proposes a deep learning approach to predicting the distal force of TSMs when manipulating a biological tissue based on only proximal-end measurements. Both Multilayer Perceptron (MLP) and Recurrent Neural Network (RNN) were investigated to study their capabilities of making sequential distal force predictions. The results were compared with those of the conventional modelling approach. It was observed that, when sufficient data was provided for training, RNN achieved the most accurate prediction (RMSE = 0.0219 N) in experiments with constant system velocity. The effects of insufficient training data, varying system velocity and irregular motion trajectories on the performance of RNN were further studied. Notably, RNN could precisely identify the current system phase in the force hysteresis profile and can be applied to TSMs with realistic non-periodic movement such as manual manipulation trajectory (RSME = 0.2287 N). The proposed approach can be applied to any TSM-driven robotic systems for accurate haptic feedback without requiring sensors at the distal ends of the robots. },
keywords = {Haptic feedback, Surgical robot, Tendon sheath mechanisms, Deep learning, Hysteresis},
language = {English},
publisher = {Elsevier Ltd.},
pages = {323-337}
}

Accurate haptic feedback is highly challenging for flexible endoscopic surgical robots due to space limitation for sensors on small end-effectors and critical force hysteresis of their tendon-sheath mechanisms (TSMs). This paper proposes a deep learning approach to predicting the distal force of TSMs when manipulating a biological tissue based on only proximal-end measurements. Both Multilayer Perceptron (MLP) and Recurrent Neural Network (RNN) were investigated to study their capabilities of making sequential distal force predictions. The results were compared with those of the conventional modelling approach. It was observed that, when sufficient data was provided for training, RNN achieved the most accurate prediction (RMSE = 0.0219 N) in experiments with constant system velocity. The effects of insufficient training data, varying system velocity and irregular motion trajectories on the performance of RNN were further studied. Notably, RNN could precisely identify the current system phase in the force hysteresis profile and can be applied to TSMs with realistic non-periodic movement such as manual manipulation trajectory (RSME = 0.2287 N). The proposed approach can be applied to any TSM-driven robotic systems for accurate haptic feedback without requiring sensors at the distal ends of the robots.

@article{schleer_2019,
title = {Evaluation of Different Modes of Haptic Guidance for Robotic Surgery},
author = {Schleer, P.; Drobinsky, S.; Radermacher, K.},
journal = {IFAC-PapersOnLine},
year = {2019},
volume = {51},
number = {34},
institution = {RWTH Aachen University, Germany},
abstract = {The evolution of surgery has resulted in a plethora of systems varying in their application field, size, as well as degree of autonomy. Especially systems which combine principles of so-called synergistic robotic systems and master-slave-telemanipulators are interesting concerning cooperative aspects of surgeon and robotic system. While the former provide haptic guidance information (“virtual fixtures”), the latter provide haptic feedback from position or force sensor information of the slave device. During the design of these combined systems particular attention has to be paid during the allocation of information to the haptic information channel as superimposing of haptic guidance information and haptic sensor feedback can lead to concealment of essential feedback information. This paper reports on an experimental usability evaluation of different haptic guidance modes varying in their degree of autonomy as well as degree of freedom (DOF) with respect to three surgical scenarios, namely reaching a predefined position and orientation, tracking a predefined 3D trajectory, and applying a defined force (such as during e.g. a 3D-bone milling task). The goal was to evaluate whether some DOF of haptic guidance information can be left free for force sensor information feedback. General findings indicate that haptic guidance does not have to be augmented on three DOF to improve usability. Therefore, a combination of haptic sensor information feedback and haptic guidance information divided between individual DOF seems to be a potential solution. },
keywords = {Robotics, Telerobotics, Telemanipulation, Robotic manipulators, Robotic surgery, Robot navigation, Trajectories, Shared Control, Guidance systems, Haptics},
language = {English},
publisher = {Elsevier Ltd.}
}

The evolution of surgery has resulted in a plethora of systems varying in their application field, size, as well as degree of autonomy. Especially systems which combine principles of so-called synergistic robotic systems and master-slave-telemanipulators are interesting concerning cooperative aspects of surgeon and robotic system. While the former provide haptic guidance information (“virtual fixtures”), the latter provide haptic feedback from position or force sensor information of the slave device. During the design of these combined systems particular attention has to be paid during the allocation of information to the haptic information channel as superimposing of haptic guidance information and haptic sensor feedback can lead to concealment of essential feedback information. This paper reports on an experimental usability evaluation of different haptic guidance modes varying in their degree of autonomy as well as degree of freedom (DOF) with respect to three surgical scenarios, namely reaching a predefined position and orientation, tracking a predefined 3D trajectory, and applying a defined force (such as during e.g. a 3D-bone milling task). The goal was to evaluate whether some DOF of haptic guidance information can be left free for force sensor information feedback. General findings indicate that haptic guidance does not have to be augmented on three DOF to improve usability. Therefore, a combination of haptic sensor information feedback and haptic guidance information divided between individual DOF seems to be a potential solution.