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@article{guo_2020,
title = {Composite learning control of robotic systems: A least squares modulated approach},
author = {Guo, K.; Pan, Y.; Zheng, D.; Yu, H.},
journal = {Automatica},
year = {2020},
month = {01},
volume = {111},
institution = {Shandong University, China; Sun Yat-sen University, China; National University of Singapore, Singapore},
abstract = {Most current studies of adaptive robot control concentrate on parameter convergence in the steady state, while parameter convergence rates are rarely investigated. This paper proposes a least-squares modulated composite learning robot control based on Moore–Penrose pseudoinverse to improve the performance of parameter convergence. In the composite learning, a prediction error is constructed based on online historical data and regressor extension, and both the prediction and tracking errors are applied to update parameter estimates such that accurate and smooth parameter estimation is obtained under a weak excitation condition termed interval excitation (IE). The distinctive features of the proposed method include: (1) Asymptotic stability of the closed-loop system is proven without the IE condition; (2) exponential stability is proven and balanced and easily tunable rates of parameter convergence are achieved under the IE condition, where the rates are independent of unpredictable excitation levels in different regressor channels. These two features are generally not achievable with the existing adaptive robot control methods. Experimental results on an industrial manipulator have demonstrated the effectiveness and superiority of the proposed approach.
},
keywords = {Adaptive control, Composite learning, Least squares, Moore–Penrose pseudoinverse, Robot manipulators},
language = {English},
publisher = {Elsevier Ltd.}
}
Abstract
Most current studies of adaptive robot control concentrate on parameter convergence in the steady state, while parameter convergence rates are rarely investigated. This paper proposes a least-squares modulated composite learning robot control based on Moore–Penrose pseudoinverse to improve the performance of parameter convergence. In the composite learning, a prediction error is constructed based on online historical data and regressor extension, and both the prediction and tracking errors are applied to update parameter estimates such that accurate and smooth parameter estimation is obtained under a weak excitation condition termed interval excitation (IE). The distinctive features of the proposed method include: (1) Asymptotic stability of the closed-loop system is proven without the IE condition; (2) exponential stability is proven and balanced and easily tunable rates of parameter convergence are achieved under the IE condition, where the rates are independent of unpredictable excitation levels in different regressor channels. These two features are generally not achievable with the existing adaptive robot control methods. Experimental results on an industrial manipulator have demonstrated the effectiveness and superiority of the proposed approach.
Vision-Based Robotic Traversal of Textureless Smooth Surfaces
Product(s):
Joint Control Robot – 6 DOF DBibTex
@article{keenan_2020,
title = {Vision-Based Robotic Traversal of Textureless Smooth Surfaces},
author = {Keenan, P.; Janabi-Sharifi, F.; Assa, A.},
journal = {IEEE Transactions on Robotics},
year = {2020},
institution = {Ryerson University, Canada; Magna International, Canada},
abstract = {This investigation focuses on servoing a robot's tool with respect to a smooth workpiece surface by making use of the surface's characteristic local differential properties. A novel formulation for 6 degree-of-freedom (DoF) textureless visual servoing based on these properties is proposed, which extends an existing 3-DoF scheme. Our approach naturally combines the geometric tools of computer-aided design and machining (CAD/CAM) theory with the manipulator control tools of visual servoing synergistically to achieve full 6-DoF pose control. A novel family of observed feature sets and their associated interaction matrices are presented. A geometric condition on the surface shape is derived under which local asymptotic stability for 6-DoF is guaranteed. Validation of the proposed method is performed in simulation and experiment using an articulated desktop robot equipped with only a monocular camera and 16 laser pointers.
},
issn = {1552-3098},
keywords = {Applied differential geometry, B-spline surfaces, robotic surface treatment, visual servoing (VS)},
language = {English},
publisher = {IEEE}
}
Abstract
This investigation focuses on servoing a robot's tool with respect to a smooth workpiece surface by making use of the surface's characteristic local differential properties. A novel formulation for 6 degree-of-freedom (DoF) textureless visual servoing based on these properties is proposed, which extends an existing 3-DoF scheme. Our approach naturally combines the geometric tools of computer-aided design and machining (CAD/CAM) theory with the manipulator control tools of visual servoing synergistically to achieve full 6-DoF pose control. A novel family of observed feature sets and their associated interaction matrices are presented. A geometric condition on the surface shape is derived under which local asymptotic stability for 6-DoF is guaranteed. Validation of the proposed method is performed in simulation and experiment using an articulated desktop robot equipped with only a monocular camera and 16 laser pointers.
A Simulation Tool for Kinematics Analysis of a Serial Robot
Product(s):
Joint Control Robot – 6 DOF DBibTex
@conference{kutuk_2019,
title = {A Simulation Tool for Kinematics Analysis of a Serial Robot},
author = {Kutuk, M.E.; Dulger, L.C.; Das, M.T.},
booktitle = {DSMIE 2019: Advances in Design, Simulation and Manufacturing },
year = {2019},
institution = {Gaziantep University, Turkey; Izmir University of Economics, Turkey; Kirrikale University, Turkey},
abstract = {Robot programming is a very significant task in the field of robotics. Off-line programming (OLP) is a method performed before robot manipulation. It is the manual editing of the robot code using computer software to simulate the real robotic scenarios. Task sequence planning, short-term production, flexibility during operation and expecting real behaviour of the robots are some of the reasons that make the users prefer OLP. Operations can be visualized in many processes such as welding, cutting, even medical applications. In this study, off-line models are offered including the forward and inverse kinematics of a six Degree-Of-Freedom (DOF) serial robot manipulator (Denso VP-6242G). Robotic Toolbox combined with GUI Development Environment in Matlab® is used for the forward kinematics solution. A Matlab® Simulink model with Simmechanics blocks is used in the inverse kinematic analysis. Visualization is enriched by 3D Solidworks® models of the robot parts. Basic motion examples that can be used in many areas are presented.
},
keywords = {Off-line programming (OLP), Denso VP-6242G, Forward and inverse kinematics, Robotic toolbox },
language = {English},
publisher = {Springe, Cham},
isbn = {978-3-030-22364-9}
}
Abstract
Robot programming is a very significant task in the field of robotics. Off-line programming (OLP) is a method performed before robot manipulation. It is the manual editing of the robot code using computer software to simulate the real robotic scenarios. Task sequence planning, short-term production, flexibility during operation and expecting real behaviour of the robots are some of the reasons that make the users prefer OLP. Operations can be visualized in many processes such as welding, cutting, even medical applications. In this study, off-line models are offered including the forward and inverse kinematics of a six Degree-Of-Freedom (DOF) serial robot manipulator (Denso VP-6242G). Robotic Toolbox combined with GUI Development Environment in Matlab® is used for the forward kinematics solution. A Matlab® Simulink model with Simmechanics blocks is used in the inverse kinematic analysis. Visualization is enriched by 3D Solidworks® models of the robot parts. Basic motion examples that can be used in many areas are presented.
An Exoskeleton Design Robotic Assisted Rehabilitation: Wrist & Forearm
Product(s):
Joint Control Robot – 6 DOF DBibTex
@conference{kutuk2_2019,
title = {An Exoskeleton Design Robotic Assisted Rehabilitation: Wrist & Forearm},
author = {Kutuk, M.E.; Das, M.T.; Dulger, L.C.},
booktitle = {2019 IFToMM World Congress on Mechanism and Machine Science},
year = {2019},
institution = {Gaziantep University, Turkey; Izmir University of Economics, Turkey; Kirrikale University, Turkey},
abstract = {Robotic systems are being used in physiotherapy for medical purposes. Providing physical training (therapy) is one of the main applications of fields of rehabilitation robotics. Upper-extremity rehabilitation involves shoulder, elbow, wrist and fingers’ actions that stimulate patients’ independence and quality of life. An exoskeleton for human wrist and forearm rehabilitation is designed and manufactured. It has three degrees of freedom which must be fitted to real human wrist and forearm. Anatomical motion range of human limbs is taken into account during design. A six DOF Denso robot is adapted. An exoskeleton driven by a serial robot has not been come across in the literature. It is feasible to apply torques to specific joints of the wrist by this way. Studies are still continuing in the subject.
},
keywords = {Robotic Rehabilitation, Wrist&Forearm, Exoskeleton },
language = {English},
publisher = {Springe, Cham},
isbn = {978-3-030-20130-2}
}
Abstract
Robotic systems are being used in physiotherapy for medical purposes. Providing physical training (therapy) is one of the main applications of fields of rehabilitation robotics. Upper-extremity rehabilitation involves shoulder, elbow, wrist and fingers’ actions that stimulate patients’ independence and quality of life. An exoskeleton for human wrist and forearm rehabilitation is designed and manufactured. It has three degrees of freedom which must be fitted to real human wrist and forearm. Anatomical motion range of human limbs is taken into account during design. A six DOF Denso robot is adapted. An exoskeleton driven by a serial robot has not been come across in the literature. It is feasible to apply torques to specific joints of the wrist by this way. Studies are still continuing in the subject.
An Enhanced IBVS Controller of a 6DOF Manipulator Using Hybrid PDSMC Method
Product(s):
Joint Control Robot – 6 DOF DBibTex
@article{li_2018,
title = {An Enhanced IBVS Controller of a 6DOF Manipulator Using Hybrid PDSMC Method},
author = {Li, S.; Ghasemi, A.; Xie, W.; Gao, Y.},
journal = {International Journal of Control, Automation and Systems},
year = {2018},
month = {04},
volume = {16},
number = {2},
institution = {Harbin Engineering University, China; Concordia University, Canada},
abstract = {The accuracy and stability are two fundamental concerns of the visual servoing control system. This paper presents an enhanced image based visual servoing (IBVS) method for increasing the accuracy of a 6DOF manipulator. The controller is designed to combine proportional derivative (PD) control with sliding mode control (SMC) on a 6DOF manipulator. The properly tuned PD controller can ensure the fast tracking performance and SMC can deal with the external disturbance and uncertainties due to the depth. The enhanced IBVS controller benefits from simple structure and easy implementation of PD control and good robustness to uncertainties of SMC. The stability of the proposed method is proven by using Lyapunov method. Simulation and experimental results are used to demonstrate the effectiveness of the proposed controller.
},
issn = {1598-6446},
keywords = {Image based visual servoing (IBVS), PD control, sliding mode control, 6DOF manipulator},
language = {English},
publisher = {Springer},
pages = {844-855}
}
Abstract
The accuracy and stability are two fundamental concerns of the visual servoing control system. This paper presents an enhanced image based visual servoing (IBVS) method for increasing the accuracy of a 6DOF manipulator. The controller is designed to combine proportional derivative (PD) control with sliding mode control (SMC) on a 6DOF manipulator. The properly tuned PD controller can ensure the fast tracking performance and SMC can deal with the external disturbance and uncertainties due to the depth. The enhanced IBVS controller benefits from simple structure and easy implementation of PD control and good robustness to uncertainties of SMC. The stability of the proposed method is proven by using Lyapunov method. Simulation and experimental results are used to demonstrate the effectiveness of the proposed controller.
Online teaching of robotic arm by human–robot interaction: end effector force/torque sensing
Product(s):
Joint Control Robot – 6 DOF DBibTex
@article{almusawi_2018,
title = {Online teaching of robotic arm by human–robot interaction: end effector force/torque sensing},
author = {Almusawi, A.R.J.; Dulger, L.C.; Kapucu, S.},
journal = {Journal of the Brazilian Society of Mechanical Sciences and Engineering},
year = {2018},
volume = {40},
number = {437},
institution = {University of Gaziantep, Turkey; University of Baghdad, Iraq},
abstract = {Human–robot interaction HRI is one of the most important research areas in robotics. A novel approach for HRI on a robotic arm is proposed by using online teaching to eliminate the effect of tool inertia. The position error is reduced in repeated motion. A multi-axis F/T sensor is attached to Denso robotic arm to measure six components of force and torque. A new controller structure is introduced by modifying the virtual spring control with tool inertia effect compensation. The human hand force and torque are transformed to the desired position/orientation (P/O) through the instantaneous matching between the direct human guidance and the robot response. The motions according to the experimental results have been compared with different teaching control variables. The results are shown significant improvement in teaching performance. The repeated motion errors are obviously reduced.
},
issn = {1806-3691},
keywords = {Human–robot interaction (HRI), Online teaching, Force/torque (F/T) sensor, Robotic arm, Inertia effect compensation (IEC)},
publisher = {Springer Berlin Heidelberg}
}
Abstract
Human–robot interaction HRI is one of the most important research areas in robotics. A novel approach for HRI on a robotic arm is proposed by using online teaching to eliminate the effect of tool inertia. The position error is reduced in repeated motion. A multi-axis F/T sensor is attached to Denso robotic arm to measure six components of force and torque. A new controller structure is introduced by modifying the virtual spring control with tool inertia effect compensation. The human hand force and torque are transformed to the desired position/orientation (P/O) through the instantaneous matching between the direct human guidance and the robot response. The motions according to the experimental results have been compared with different teaching control variables. The results are shown significant improvement in teaching performance. The repeated motion errors are obviously reduced.
Forward and Inverse Kinematics Analysis of Denso Robot
Product(s):
Joint Control Robot – 6 DOF DBibTex
@inproceedings{kutuk_2017,
title = {Forward and Inverse Kinematics Analysis of Denso Robot},
author = {Kutuk, M.E.; Das, M.T.; Dulger, L.C.},
booktitle = {Proceedings of the International Symposium of Mechanism and Machine Science, 2017},
year = {2017},
institution = {University of Gaziantep, Turkey; University of Kirikkale, Turkey},
abstract = {A forward and inverse kinematic analysis of 6 axis DENSO robot with closed form solution is performed in this paper. Robotics toolbox provides a great simplicity to us dealing with kinematics of robots with the ready functions on it. However, making calculations in traditional way is important to dominate the kinematics which is one of the main topics of robotics. Robotic toolbox in Matlab® is used to model Denso robot system. GUI studies including Robotic Toolbox are given with simulation examples.
},
keywords = {Robot Kinematics, Simulation, Denso Robot, Robotic Toolbox, GUI},
language = {English},
pages = {71-78}
}
Abstract
A forward and inverse kinematic analysis of 6 axis DENSO robot with closed form solution is performed in this paper. Robotics toolbox provides a great simplicity to us dealing with kinematics of robots with the ready functions on it. However, making calculations in traditional way is important to dominate the kinematics which is one of the main topics of robotics. Robotic toolbox in Matlab® is used to model Denso robot system. GUI studies including Robotic Toolbox are given with simulation examples.
Real time optimum trajectory generation for redundant/hyper-redundant serial industrial manipulators
Product(s):
Joint Control Robot – 6 DOF DBibTex
@article{ayten_2017,
title = {Real time optimum trajectory generation for redundant/hyper-redundant serial industrial manipulators},
author = {Ayten, K.K.; Sahinkaya, M.N.; Dumlu, A.},
journal = {International Journal of Advanced Robotic Systems},
year = {2017},
volume = {14},
number = {6},
institution = {Erzurum Technical University, Turkey; Kingston University, UK; },
abstract = {This article presents an optimization technique to develop minimum energy consumption trajectories for redundant/hyper-redundant manipulators with predefined kinematic and dynamic constraints. The optimization technique presents and combines two novel methods for trajectory optimization. In the first method, the system’s kinematic and dynamic constraints are handled in a sequential manner within the cost function to avoid running the inverse dynamics when the constraints are not satisfied. Thus, the complexity and computational effort of the optimization algorithm is significantly reduced. For the second method, a novel virtual link concept is introduced to replace all the redundant links to eliminate physical impossible configurations before running the inverse dynamic model for the trajectory optimization. The method is verified on a three-degree of freedom redundant manipulator and the result is also demonstrated with computer simulations based on an 8-link planar hyper-redundant manipulator.
},
keywords = {Optimum trajectory planning, energy minimization, constraint handling, cost function, redundant manipulators, hyper-redundant manipulator, virtual link},
language = {English},
publisher = {SAGE}
}
Abstract
This article presents an optimization technique to develop minimum energy consumption trajectories for redundant/hyper-redundant manipulators with predefined kinematic and dynamic constraints. The optimization technique presents and combines two novel methods for trajectory optimization. In the first method, the system’s kinematic and dynamic constraints are handled in a sequential manner within the cost function to avoid running the inverse dynamics when the constraints are not satisfied. Thus, the complexity and computational effort of the optimization algorithm is significantly reduced. For the second method, a novel virtual link concept is introduced to replace all the redundant links to eliminate physical impossible configurations before running the inverse dynamic model for the trajectory optimization. The method is verified on a three-degree of freedom redundant manipulator and the result is also demonstrated with computer simulations based on an 8-link planar hyper-redundant manipulator.
A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)
Product(s):
Joint Control Robot – 6 DOF DBibTex
@article{almusawi_2016,
title = {A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)},
author = {Almusawi, A.R.J.; Dulger, L.C.; Kapucu, S.},
journal = {Computatational Intelligence and Neuroscience},
year = {2016},
volume = {2016},
institution = {University of Gaziantep, Turkey; University of Baghdad, Iraq},
abstract = {This paper presents a novel inverse kinematics solution for robotic arm based on Artificial Neural Network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robotÍs joint angles.
},
keywords = {Artificial neural network, Motion control, Robotic arm, Inverse kinematics},
language = {English}
}
Abstract
This paper presents a novel inverse kinematics solution for robotic arm based on Artificial Neural Network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robotÍs joint angles.
An Acceleration Command Approach to Robotic Stereo Image-based Visual Servoing
Product(s):
Joint Control Robot – 6 DOF DBibTex
@inproceedings{mohebbi_2016_2,
title = {An Acceleration Command Approach to Robotic Stereo Image-based Visual Servoing},
author = {Mohebbi, A.; Keshmiri, M.; Xie, W.-F.},
booktitle = {Proceedings of the 19th World Congress The International Federation of Automatic Control (IFAC)},
year = {2016},
volume = {47},
number = {3},
institution = {Concordia University, Department of Mechanical and Industrial Engineering, Montreal, QC, Canada},
abstract = {This paper presents a new stereo image-based visual servoing (IBVS) controller for a six degrees of freedom (DOF) robot manipulator based on acceleration command. An eye-in-hand stereo vision system is utilized to capture the images of the object and to estimate the depth of the object. A proportional derivative (PD) controller is developed considering the acceleration command. The augmented image-based visual servoing (AIBVS) controller helps the system achieve smoother and more linear image feature trajectories and decrease the risk that the features leave the field of view (FOV). The developed control method also enhances the stability characteristics of the system and the robotÍs endeffector 3D behaviour. Both simulation and experimental results on a 6 DOF DENSO 6242G robot validate the effectiveness of the proposed stereo AIBVS controller. The comparison with IBVS with monocular vision system demonstrates the improved performance of the proposed system.
},
keywords = {Stereo Visual Servoing, eye-in-hand, Image-based, Acceleration command, depth estimation},
language = {English},
publisher = {IFAC},
pages = {7239_7245}
}
Abstract
This paper presents a new stereo image-based visual servoing (IBVS) controller for a six degrees of freedom (DOF) robot manipulator based on acceleration command. An eye-in-hand stereo vision system is utilized to capture the images of the object and to estimate the depth of the object. A proportional derivative (PD) controller is developed considering the acceleration command. The augmented image-based visual servoing (AIBVS) controller helps the system achieve smoother and more linear image feature trajectories and decrease the risk that the features leave the field of view (FOV). The developed control method also enhances the stability characteristics of the system and the robotÍs endeffector 3D behaviour. Both simulation and experimental results on a 6 DOF DENSO 6242G robot validate the effectiveness of the proposed stereo AIBVS controller. The comparison with IBVS with monocular vision system demonstrates the improved performance of the proposed system.
Robust On-Line Model Predictive Control for a Constrained Image Based Visual Servoing
Product(s):
Joint Control Robot – 6 DOF DBibTex
@article{hajiloo_2015,
title = {Robust On-Line Model Predictive Control for a Constrained Image Based Visual Servoing},
author = {Hajiloo, A.; Keshmiri, M.; Xie, W.-F.; Wang, T.-T.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2015},
abstract = {This paper presents an on_line image based visual servoing (IBVS) controller for a 6 DOF robotic system based on the robust model predictive control (RMPC) method. The controller is designed considering the robotic visual servoing systemÍs input and output constraints, such as robot physical limitations and visibility constraints. The proposed IBVS controller avoids the inverse of the image Jacobian matrix and hence can solve the intractable problems for the classical IBVS controller, such as large displacements between the initial and the desired positions of the camera. To verify the effectiveness of the proposed algorithm, real_time experimental results on a 6 Degrees_of_Freedom (DOF) robot manipulator with eye_in_hand configuration are presented and discussed.
},
issn = {0278-0046},
keywords = {Image Based Visual Servoing, Model Predictive Controller (MPC), Robotic, Visual Servoing},
language = {English},
publisher = {IEEE}
}
Abstract
This paper presents an on_line image based visual servoing (IBVS) controller for a 6 DOF robotic system based on the robust model predictive control (RMPC) method. The controller is designed considering the robotic visual servoing systemÍs input and output constraints, such as robot physical limitations and visibility constraints. The proposed IBVS controller avoids the inverse of the image Jacobian matrix and hence can solve the intractable problems for the classical IBVS controller, such as large displacements between the initial and the desired positions of the camera. To verify the effectiveness of the proposed algorithm, real_time experimental results on a 6 Degrees_of_Freedom (DOF) robot manipulator with eye_in_hand configuration are presented and discussed.
Augmented Image-Based Visual Servoing of a Manipulator Using Acceleration Command
Product(s):
Joint Control Robot – 6 DOF DBibTex
@article{keshmiri_2014,
title = {Augmented Image-Based Visual Servoing of a Manipulator Using Acceleration Command},
author = {Keshmiri, M.; Wen-Fang Xie; Mohebbi, A.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2014},
volume = {61},
number = {10},
abstract = {This paper presents a new image-based visual servoing (IBVS) controller named augmented IBVS for a 6-DOF manipulator. The main idea of this controller is that it produces acceleration as the controlling command. A proportional-derivative controller is developed to provide the robot with the controlling command. This controller can achieve a smoother and more linear feature trajectory in the image space and decrease the risk that the features leave the field of view. The developed control method also enhances the camera trajectory in 3-D space. The stability of the proposed method is fully investigated by using the Lyapunov method and the perturbed systems theory. Experimental tests are performed on a 6-DOF robotic system to validate the effectiveness of the proposed controller. The performance of the controller is compared with that of a conventional IBVS.
},
issn = {0278-0046},
keywords = {Image-based visual servoing (IBVS), Lyapunov stability, robotic, visual servoing},
language = {English},
publisher = {IEEE},
pages = {5444-5452}
}
Abstract
This paper presents a new image-based visual servoing (IBVS) controller named augmented IBVS for a 6-DOF manipulator. The main idea of this controller is that it produces acceleration as the controlling command. A proportional-derivative controller is developed to provide the robot with the controlling command. This controller can achieve a smoother and more linear feature trajectory in the image space and decrease the risk that the features leave the field of view. The developed control method also enhances the camera trajectory in 3-D space. The stability of the proposed method is fully investigated by using the Lyapunov method and the perturbed systems theory. Experimental tests are performed on a 6-DOF robotic system to validate the effectiveness of the proposed controller. The performance of the controller is compared with that of a conventional IBVS.
Novel two-stage control scheme for robust constrained visual servoing
Product(s):
Joint Control Robot – 6 DOF DBibTex
@conference{assa_2014,
title = {Novel two-stage control scheme for robust constrained visual servoing},
author = {Assa, A.; Janabi-Sharifi, F.},
booktitle = {2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014)},
year = {2014},
abstract = {Visual servoing techniques are proven to be beneficial in unstructured workspaces. However, visual servoing is bounded by several constraints and is prone to the uncertainties of the system, leaving it of limited applicability. Several previous works have tackled these problems; yet, most of these works considered only a partial set of the aforementioned shortcomings. This work proposes a novel two-stage controller that is capable of minimizing the uncertainties of the system, while handling the constraints properly. The effectiveness of the controller is put into test via various simulations and experiments. The experimental results confirm the usefulness and applicability of this controller.
},
language = {English},
publisher = {IEEE},
pages = {749 - 754}
}
Abstract
Visual servoing techniques are proven to be beneficial in unstructured workspaces. However, visual servoing is bounded by several constraints and is prone to the uncertainties of the system, leaving it of limited applicability. Several previous works have tackled these problems; yet, most of these works considered only a partial set of the aforementioned shortcomings. This work proposes a novel two-stage controller that is capable of minimizing the uncertainties of the system, while handling the constraints properly. The effectiveness of the controller is put into test via various simulations and experiments. The experimental results confirm the usefulness and applicability of this controller.
Reduced jerk joint space trajectory planning method using 5-3-5 spline for robot manipulators
Product(s):
Joint Control Robot – 6 DOF DBibTex
@conference{porawagama_2014,
title = {Reduced jerk joint space trajectory planning method using 5-3-5 spline for robot manipulators},
author = {Porawagama, C.D.; Munasinghe, S.R.},
booktitle = {2014 7th International Conference on Information and Automation for Sustainability (ICIAfS)},
year = {2014},
institution = {Department of Electronic and Telecommunication Engineering, University of Moratuwa, Sri Lanka},
abstract = {A new trajectory planning method for generating bounded and continuous jerk trajectories in joint space has been developed and tested. In manipulator trajectory planning, reduced jerk trajectories are desired for path tracking and vibration suppression. The proposed interpolation algorithm in this research generates a spline, composed with 5th-order, 3rdorder and 5th-order polynomial segments (5-3-5 spline) which can be used for point-to-point trajectories and trajectories with via points. The generated trajectories are continuously differentiable in position, velocity, acceleration, and has a start and end zero bounded continuous jerk profile. The algorithm allows the user to independently define the position, velocity, acceleration and jerk values at both start and end points, via point positions and velocities. These user definable parameters in the proposed 5-3-5 spline algorithm gives the flexibility for generating trajectories for various motion characteristics. Generated trajectories were tested successfully on DENSO VP6 robot arm. The experimental results are presented.
},
issn = {2151-1802 },
keywords = {motion with via points, Robot manipulators, joint space, trajectory planning, reduced jerk, continuous acceleration, piecewise polynomials, 5-3-5 spline trajectory, interpolation algorithm, point-to-point motion},
language = {English},
publisher = {IEEE},
isbn = {978-1-4799-4598-6 }
}
Abstract
A new trajectory planning method for generating bounded and continuous jerk trajectories in joint space has been developed and tested. In manipulator trajectory planning, reduced jerk trajectories are desired for path tracking and vibration suppression. The proposed interpolation algorithm in this research generates a spline, composed with 5th-order, 3rdorder and 5th-order polynomial segments (5-3-5 spline) which can be used for point-to-point trajectories and trajectories with via points. The generated trajectories are continuously differentiable in position, velocity, acceleration, and has a start and end zero bounded continuous jerk profile. The algorithm allows the user to independently define the position, velocity, acceleration and jerk values at both start and end points, via point positions and velocities. These user definable parameters in the proposed 5-3-5 spline algorithm gives the flexibility for generating trajectories for various motion characteristics. Generated trajectories were tested successfully on DENSO VP6 robot arm. The experimental results are presented.
Ultrasound Guided Robot for Minimally Invasive Surgery
Product(s):
Joint Control Robot – 6 DOF DBibTex
@article{rafalovich,
title = {Ultrasound Guided Robot for Minimally Invasive Surgery},
author = {Rafalovich, A.; Kosa, G.},
journal = {Ultrasound},
volume = {60},
number = {80},
institution = {School of Mechanical Engineering, Tel-Aviv University, Israel},
abstract = {One of the difficulties of guiding a medical robot with an ultrasound is the need to be in the imaging area of the ultrasound. Our solution to this problem is to locate the ultrasonic sensor at the tip of the tool driven by the medical robot. By using a miniature ultrasonic sensor, It is possible to achieve high precision localized measurements.
},
language = {English}
}
Abstract
One of the difficulties of guiding a medical robot with an ultrasound is the need to be in the imaging area of the ultrasound. Our solution to this problem is to locate the ultrasonic sensor at the tip of the tool driven by the medical robot. By using a miniature ultrasonic sensor, It is possible to achieve high precision localized measurements.