This body of research is built around the development of a roaming robot for indoor settings. Quanser's ground robotics system, QBot 2e, was utilized to map parts of a room along with collecting temperature and light intensity data while automatically navigating around various obstacles. Our research includes characterization of drift in obstacle mapping, heading correction, integration of sensors, and pathfinding. The models used were implemented in MATLAB and Simulink using QUARC and run on an onboard Raspberry Pi in the QBot 2e.

A transmissibility is a mathematical model that relates a subset of a system's outputs to another subset of outputs of the same system without knowledge of the external excitation or the dynamics of the system. This study investigates fault detection, localization, and mitigation of connected autonomous vehicles (CAV) platoons using transmissibility operators. A CAV platoon is a network of connected autonomous vehicles that communicate together to move in a specific path with a desired velocity. % Failure in a physical component of a vehicle, or failure in the form of an {internal delay}, a cyber-attack, or a communication time-delay affects the safety and security of the CAV platoons. % In this paper, we use measurements from sensors available in CAV platoons to identify transmissibility operators, which are used for health monitoring, fault localization, and fault mitigation in the platoon. We first consider the case of vehicle-to-cloud communication (V2C) to monitor the platoon health. Then, we assume that the platoon loses communication with the cloud, and we monitor the health of the platoon based on vehicle-to-vehicle (V2V) communication. We apply the proposed technique to a model of the platoon obtained using the bond graph approach, and an experimental setup consisting of three connected autonomous robots.

This paper proposes a control strategy integrating the non‐linear extended state observer (NLESO) and the non‐singular terminal sliding mode control (NTSMC) for the trajectory tracking of wheeled mobile robots subject to bounded disturbances. A new transformation method of chained model in terms of Lie derivative is presented to simplify the controller design. A specific NLESO combining linear term and non‐linear term is designed to estimate the disturbances with a faster convergence performance. A scheme for determining the gain range of NLESO is explicitly given to facilitate the tuning of experimental parameters. Meanwhile, the NTSMC achieves finite time convergence of the tracking error system and the chattering phenomenon in NTSMC is dramatically alleviated with the compensation from NLESO. The experimental results validate the strong robustness and good performance of the proposed control strategy.

This paper considered the persistent real-time localization problem of dynamic multi-agent systems with repetitive running characteristics under directed graph. The trajectory length of the agent is randomly varying caused by system constraints and external environment. A novel distributed iterative learning localization estimation method with full historical average data compensation is designed. The average value of all available historical data in the previous operations is used to compensate the incomplete trajectory. The designed diagnosis mechanism and search mechanism are used to determine whether the agent has stopped running and to screen out the available historical data. Considering that the trajectory of agent will become stable with the increase of operations, and in order to reduce the computational burden, an improved distributed localization algorithm with receding horizon historical average data compensation is proposed. The asymptotic convergence of the estimation algorithms in the sense of mathematical expectation is derived through the rigorous analysis. Meanwhile, the influence of the incomplete repetitive trajectory of the agent on estimation error and convergence rate is also analyzed. The numerical simulation result shows the validity of the proposed methods and the experimental result based on QBot-2e robot platform verifies the realizability of the proposed method.

The need to design a robust, accurate and lightweight real-time control architecture for a low-cost embedded system has become a necessary step in robotics applications. Therefore, the goal of this work is to design an integrated and accurate control system for a differential wheeled mobile robot. A hierarchical control approach has been adopted in this work which, takes into account the sub-systems controller of the problem related to robot path tracking. To this end, the control structure includes the design of a sliding mode control (SMC) scheme to stabilize the robot and precisely track the path that matches the kinematics of the mechanical structure. Moreover, the control structure provides a new design of the DC motor controller for optimum performance. To obtain an integrated control system for automated tasks, an accurate position estimation and an optimized high-level path planning algorithm have been proposed. The robustness and performance of the approved control and estimation systems have been verified through real-time implementations in different experiments. The results show the high accuracy of the robot’s tracking on different paths.

This paper illustrates the conducted efforts for deploying an interactive project-based learning for robotics course using MATLAB. This project is part of a first course on robotics at the graduate level. The course combines both the theoretical and practical aspects to achieve its goals. The course consists of a set of laboratory sessions ends with a class project, these labs experimentally illustrate the modeling, simulation, path-planning and control of the Robot, using the robotics toolbox under MATLAB tools as well as physical interaction with the different robot platforms. The interaction between the student and the physical robot platforms is finally addressed in the class project; in this project, two tasks are considered. The first one is to control a 5DoF robot manipulator to perform a pick and place task. Initially the task is simulated under MATLAB robotics toolbox; the robot is commended to pick objects from initially known poses and stacks them in target poses. Furthermore, the robot manipulator in the second part of the project, with the aid of a vision system, is commended to work as an autonomous robotic arm that picks up colored objects, and then places them in different poses, based on their identified colors. The demonstrated results from the course evolution and assessment tools reflect the benefits of high-level deployment of robot platform in interactive project based learning to increase the students' performance in the course, about 100% and 75% of the student groups successfully completed the required tasks in the project first part and second part respectively.

This paper investigates the formation control problem for linear multi-agent systems under switching directed topologies. Based on absolute or relative outputs, we propose two distributed observer-based event-triggered control schemes. Both schemes can guarantee the boundedness of formation errors under sufficient conditions. The schemes can also avoid Zeno behaviors by giving an estimation for the lower bound of sampling intervals. Finally, simulations and experiments validate the proposed approaches.

In this paper a robust tracking control strategy is proposed for Unicycle Mobile Robots (UMRs) under the influence of some disturbances. The proposed strategy is designed taking into account the perturbed kinematic model and it is based on two robust control techniques: Sliding-Mode Control (SMC) and Attractive Ellipsoid Method (AEM). The control of the heading angle is designed by means of a saturated SMC algorithm while the position control is designed by means of the AEM considering a Barrier Lyapunov function (BLF) approach. Simulation results illustrate the performance of the proposed robust controller compared to a classic UMR controller. Finally, some experimental results and comparisons illustrate the performance of the proposed strategy.

@article{mera_2020,
title = {A sliding-mode based controller for trajectory tracking of perturbed Unicycle Mobile Robots},
author = {Mera, M.; Ríos, H.; Martínez, E.A.},
journal = {Control Engineering Practice},
year = {2020},
month = {09},
volume = {102},
institution = {Instituto Politécnico Nacional, Mexico; Tecnológico Nacional de México/I.T. La Laguna, Mexico},
abstract = {In this work a tracking robust algorithm for the perturbed kinematic model of an Unicycle Mobile Robot (UMR) is proposed. The control design is based on the well-known first order sliding mode control approach, with a modification that helps to reduce the chattering effect. This strategy takes into account perturbations and consider any admissible (with respect to the nonholonomic constraints) smooth reference trajectory, ensuring the convergence of the tracking error dynamics to the origin asymptotically. The resulting control input is a discontinuous switched function. Its implementability is validated through experiments using a QBot2 and compared with standard well-established control design methods for this problem. },
keywords = {Sliding-modes control, Mobile Robots, Tracking},
language = {English},
publisher = {Elsevier Ltd.}
}

In this work a tracking robust algorithm for the perturbed kinematic model of an Unicycle Mobile Robot (UMR) is proposed. The control design is based on the well-known first order sliding mode control approach, with a modification that helps to reduce the chattering effect. This strategy takes into account perturbations and consider any admissible (with respect to the nonholonomic constraints) smooth reference trajectory, ensuring the convergence of the tracking error dynamics to the origin asymptotically. The resulting control input is a discontinuous switched function. Its implementability is validated through experiments using a QBot2 and compared with standard well-established control design methods for this problem.

The paper presents research on methods of a wheeled mobile robot localization using an optical motion capture system. The results of localization based on the model of forward kinematics and odometric measurements were compared. A pure pursuit controller was used to control the robot’s behaviour in the path following tasks. The paper describes a motion capture system based on infrared cameras, including the calibration method. In addition, a method for determining the accuracy of robot location using the motion capture system, based on the Hausdorff distance, was proposed. As a result of the research it was found that the Hausdorff distance is very useful in determining the accuracy of localization of wheeled robots, especially those described by differential drive kinematics.

@conference{khalil_2020,
title = {Fault Detection, Localization, and Mitigation of a Network of Connected Autonomous Vehicles Using Transmissibility Identification},
author = {Khalil, A.; Al Janaideh, M.; Aljanaideh, K.F.; Kundur, D. },
booktitle = {2020 American Control Conference},
year = {2020},
institution = {Memorial University, Canada; University of Michigan, USA; University of Toronto, Canada},
abstract = {This paper investigates fault detection, localization, and mitigation of autonomous vehicles platoons. The platoon is a network of autonomous vehicles that communicate together to move in a desired way. A fault in an autonomous vehicles platoon is a failure in either a physical component of a vehicle or a communication link between two vehicles in the platoon. This failure may lead to damage in one or more of the autonomous vehicles. Model-based health monitoring of a network of vehicles requires knowledge of a model of the system and the excitation signal, and thus may not be applicable. In this paper, we use measurements from available sensors in the platoon to identify sensor-to-sensor models that can be used for health monitoring, fault localization, and fault mitigation in the platoon. The dynamics of the network and the vehicles and the excitation signal that acts on the platoon are assumed to be unknown. We apply the proposed approach to a model of a platoon of autonomous vehicles and an experimental setup consisting of a platoon of three autonomous robots. },
issn = {0743-1619 },
keywords = {Autonomous vehicles, Finite impulse response filters, Actuators, Sensor systems, Delay effects, Cyberattack},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-8267-8}
}

This paper investigates fault detection, localization, and mitigation of autonomous vehicles platoons. The platoon is a network of autonomous vehicles that communicate together to move in a desired way. A fault in an autonomous vehicles platoon is a failure in either a physical component of a vehicle or a communication link between two vehicles in the platoon. This failure may lead to damage in one or more of the autonomous vehicles. Model-based health monitoring of a network of vehicles requires knowledge of a model of the system and the excitation signal, and thus may not be applicable. In this paper, we use measurements from available sensors in the platoon to identify sensor-to-sensor models that can be used for health monitoring, fault localization, and fault mitigation in the platoon. The dynamics of the network and the vehicles and the excitation signal that acts on the platoon are assumed to be unknown. We apply the proposed approach to a model of a platoon of autonomous vehicles and an experimental setup consisting of a platoon of three autonomous robots.

@inbook{yazdjerdi_2020,
title = {Fault Tolerant Controller Schemes for Single and Multiple Mobile Robots},
author = {Yazdjerdi, P.; Meskin N. },
booktitle = {Soft Computing in Condition Monitoring and Diagnostics of Electrical and Mechanical Systems},
year = {2020},
institution = {Qatar University, Qatar},
abstract = {In this chapter, an actuator fault tolerant controller is developed for both single and multiple differential drive mobile robots. First, a fault tolerant controller is proposed for loss of effectiveness actuator faults in differential drive mobile robots while tracking the desired trajectory. The actuator loss of effectiveness fault is injected on the kinematic equation of the robot as a multiplicative gain in the left and right wheels angular velocity. Accordingly, the goal is to estimate and tolerate the injected actuator faults. A fault diagnosis method based on joint state and parameter estimation scheme is proposed to estimate the actuator loss of effectiveness gains as well as the states of the system. The estimated values of actuator faults are then used in the controller to compensate their effects on the mobile robots performance. Next, the proposed Fault Tolerant Controller (FTC) method is extended for the leader–follower formation control of mobile robots in the presence of actuator fault in a leader and followers robots. An Extended Kalman Filter (EKF) is utilized for each robot to obtain the parameters and states of the system and as the actuator fault is detected in any of the robots, the corresponding controller compensates the fault. Finally, an obstacle avoidance feature is added to the designed actuator fault tolerant controller, for single mobile robot. Toward this goal, a go-to goal controller is designed for the mobile robot to reach the desired destination. Meanwhile, the robot can detect any obstacle with a given color specification using Kinect sensor mounted on the robot and consequently avoid collisions. The efficacy of the proposed FTC framework is demonstrated for both single and multiple mobile robots by real-time simulation and implementation on Qbot-2 from Quanser. },
language = {English},
series = {Advances in Intelligent Systems and Computing},
publisher = {Springer, Singapore},
isbn = {978-981-15-1532-3}
}

In this chapter, an actuator fault tolerant controller is developed for both single and multiple differential drive mobile robots. First, a fault tolerant controller is proposed for loss of effectiveness actuator faults in differential drive mobile robots while tracking the desired trajectory. The actuator loss of effectiveness fault is injected on the kinematic equation of the robot as a multiplicative gain in the left and right wheels angular velocity. Accordingly, the goal is to estimate and tolerate the injected actuator faults. A fault diagnosis method based on joint state and parameter estimation scheme is proposed to estimate the actuator loss of effectiveness gains as well as the states of the system. The estimated values of actuator faults are then used in the controller to compensate their effects on the mobile robots performance. Next, the proposed Fault Tolerant Controller (FTC) method is extended for the leader–follower formation control of mobile robots in the presence of actuator fault in a leader and followers robots. An Extended Kalman Filter (EKF) is utilized for each robot to obtain the parameters and states of the system and as the actuator fault is detected in any of the robots, the corresponding controller compensates the fault. Finally, an obstacle avoidance feature is added to the designed actuator fault tolerant controller, for single mobile robot. Toward this goal, a go-to goal controller is designed for the mobile robot to reach the desired destination. Meanwhile, the robot can detect any obstacle with a given color specification using Kinect sensor mounted on the robot and consequently avoid collisions. The efficacy of the proposed FTC framework is demonstrated for both single and multiple mobile robots by real-time simulation and implementation on Qbot-2 from Quanser.

@article{chang_2020,
title = {Fixed-Time Active Disturbance Rejection Control and Its Application to Wheeled Mobile Robots},
author = {Chang, S.; Wang, Y.; Zuo, Z.},
journal = { IEEE Transactions on Systems, Man, and Cybernetics: Systems},
year = {2020},
institution = {Tianjin University, China},
abstract = {This article is concerned with the fixed-time active disturbance rejection control approach for nonlinear systems subject to uncertainties and disturbances. First, a new type of extended state observer (ESO) which can attain fixed-time convergence is established to estimate the states and the total disturbance. Then a fixed-time controller based on the above ESO is developed to achieve high precision control performance. Finally, the proposed method is utilized for the wheeled mobile robot where the experiment validates the effectiveness of the theoretical results. },
issn = {2168-2216},
keywords = {Active disturbance rejection control (ADRC), fixed-time controller (FTC), fixed-time extended state observer (ESO), wheeled mobile robot (WMR)},
language = {English},
publisher = {IEEE}
}

This article is concerned with the fixed-time active disturbance rejection control approach for nonlinear systems subject to uncertainties and disturbances. First, a new type of extended state observer (ESO) which can attain fixed-time convergence is established to estimate the states and the total disturbance. Then a fixed-time controller based on the above ESO is developed to achieve high precision control performance. Finally, the proposed method is utilized for the wheeled mobile robot where the experiment validates the effectiveness of the theoretical results.

@article{tran_2020,
title = {Formation Control With Multiplex Information Networks},
author = {Tran, D.; Yucelen, T.; Pasiliao, E.L.},
journal = {IEEE Transactions on Control Systems Technology},
year = {2020},
institution = {University of South Florida, USA; Air Force Research Laboratory, USA},
abstract = {Current distributed control methods have a lack of information exchange infrastructure to enable spatially evolving multiagent formations. Specifically, these methods are designed based on information exchange rules represented by a network having a single layer, where they lead to multiagent formations with fixed, nonevolving spatial properties. For situations where capable agents have to control the resulting formation through these methods, they can often do so if such agents have global information exchange ability. Yet, global information exchange is not practical for cases that have large numbers of agents and low-bandwidth peer-to-peer communications. Motivated from this standpoint, the contribution of this paper is to show how information exchange rules, which are represented by a network having multiple layers (multiplex information networks), can be designed for enabling spatially evolving multiagent formations. In particular, we first consider the formation assignment problem and then the formation tracking problem and introduce new distributed control architectures that allow capable agents to spatially alter the size and the orientation of the resulting formation without requiring global information exchange ability. In addition, tools and methods from differential potential fields are further utilized in order to generalize the proposed distribute control architecture for the formation tracking problem to allow for connectivity maintenance and collision avoidance needed in real-world applications. Stability of the proposed architectures is theoretically analyzed and their efficacy is illustrated on numerical examples and on multiagent formation experiments. },
issn = {1063-6536},
keywords = {Collision avoidance, connectivity maintenance, distributed control, formation control, multiagent systems, multplex information networks},
language = {English},
publisher = {IEEE}
}

Current distributed control methods have a lack of information exchange infrastructure to enable spatially evolving multiagent formations. Specifically, these methods are designed based on information exchange rules represented by a network having a single layer, where they lead to multiagent formations with fixed, nonevolving spatial properties. For situations where capable agents have to control the resulting formation through these methods, they can often do so if such agents have global information exchange ability. Yet, global information exchange is not practical for cases that have large numbers of agents and low-bandwidth peer-to-peer communications. Motivated from this standpoint, the contribution of this paper is to show how information exchange rules, which are represented by a network having multiple layers (multiplex information networks), can be designed for enabling spatially evolving multiagent formations. In particular, we first consider the formation assignment problem and then the formation tracking problem and introduce new distributed control architectures that allow capable agents to spatially alter the size and the orientation of the resulting formation without requiring global information exchange ability. In addition, tools and methods from differential potential fields are further utilized in order to generalize the proposed distribute control architecture for the formation tracking problem to allow for connectivity maintenance and collision avoidance needed in real-world applications. Stability of the proposed architectures is theoretically analyzed and their efficacy is illustrated on numerical examples and on multiagent formation experiments.

Homing of a robot is characterized as its travelling through a path to perform an assigned task and returning to its home position or underlying position. The paper centers on the idea of programming a wheeled mobile robot for automating homing by path planning, obstacle avoidance and control. The proposed homing scheme is designed by modifying existing search algorithms. A comprehensive comparison of 4 different algorithms is also executed and presented in the paper. Of which best suited algorithm is modified and applied to a Quanser Qbot 2e experimental platform. The QBot leverages Quanser Rapid Control Prototyping software which can seamlessly integrate with MATLAB/ Simulink software to provide real time communication. The experiment has demonstrated that the suggested algorithm achieves homing accurately, with automation.

Currently, there are multiple packages available to implement different Simultaneous Localisation And Mapping (SLAM) approaches in Robot Operating System (ROS). To effectively obtain sensor data, these packages use parameters whose values are set from prior knowledge and experience working with robots and SLAM. In this research, using a Multi-Objective Genetic Algorithm (MOGA) to optimise the values for these parameters is proposed. Using MOGA allows trade-offs between the objectives using Pareto dominance technique. Three parameters from the RTAB-Map package are considered for optimisation using three different MOGA mechanisms, Dominance Count, Dominance Rank and Switching Fitness. The quality of the map generated for every set of parameters is taken as the indicator of its performance. The number of corners, number of contours and the proportion of occupied cells in the map are used as quantitative measures of map quality. Finally, results obtained from the algorithm are tested on a Quanser QBot2 robot.

An autonomous vehicle platoon is a network of autonomous vehicles that communicate together to move in a desired way. One of the greatest threats to the operation of an autonomous vehicle platoon is the failure of either a physical component of a vehicle or a communication link between two vehicles. This failure affects the safety and stability of the autonomous vehicle platoon. Transmissibility-based health monitoring uses available sensor measurements for fault detection under unknown excitation and unknown dynamics of the network. After a fault is detected, a sliding mode controller is used to mitigate the fault. Different fault scenarios are considered including vehicle internal disturbances, cyber attacks, and communication delays. We apply the proposed approach to a bond graph model of the platoon and an experimental setup consisting of three autonomous robots.

@article{huang_2019,
title = {A PSO-tuned Fuzzy Logic System for Position Tracking of Mobile Robot},
author = {Huang, C.; Farooq, U.; Liu, H.; Gu, J.; Luo, J.},
journal = {International Journal of Robotics and Automation},
year = {2019},
volume = {206},
abstract = {In this paper, we proposed a simple but practical fuzzy logic position tracking controller for a wheeled mobile robot. Certain mobile robot with symmetric or ignorable body shape may focus on its position precision on a path tracking task. In this case, we assigned its position errors as input of our fuzzy logic controller and its linear and angular velocities as outputs. Then, we optimized it by tuning the parameters of scaling and membership functions using a particle swarm optimization. Our fuzzy logic system was optimized and simulated in Matlab and Simulink and was experimentally tested on Quanser’s Qbot2 robot with Quarc control system. After optimization, the values of Fitness Function (cumulative position errors) have distinctly decreased from 35.9642 to 5.8246 in simulation and from 37.4041 to 7.3935 experimentally. These results had shown that the optimized system outperformed the same system without optimization. },
language = {English},
publisher = {Acta Press}
}

In this paper, we proposed a simple but practical fuzzy logic position tracking controller for a wheeled mobile robot. Certain mobile robot with symmetric or ignorable body shape may focus on its position precision on a path tracking task. In this case, we assigned its position errors as input of our fuzzy logic controller and its linear and angular velocities as outputs. Then, we optimized it by tuning the parameters of scaling and membership functions using a particle swarm optimization. Our fuzzy logic system was optimized and simulated in Matlab and Simulink and was experimentally tested on Quanser’s Qbot2 robot with Quarc control system. After optimization, the values of Fitness Function (cumulative position errors) have distinctly decreased from 35.9642 to 5.8246 in simulation and from 37.4041 to 7.3935 experimentally. These results had shown that the optimized system outperformed the same system without optimization.

@article{zheng_2019,
title = {Finite-time control of mobile robot systems with unmeasurable angular and linear velocities via bioinspired neurodynamics approach},
author = {Zheng, W.; Wang, H.; Sun, F.; Li, X.; Wen, S.},
journal = {Applied Soft Computing},
year = {2019},
month = {12},
volume = {85},
institution = {Yanshan University, China; Tsinghua University, China; Nanyang Technological University, China},
abstract = {This paper addresses the stability analysis and adaptive robust finite-time bioinspired neurodynamics control for a class of mobile robot systems with unmeasurable angular and linear velocities, and time-varying bounded disturbance. The error system of the mobile robot is decomposed into two subsystems based on the system model. The state feedback control laws with observers are designed for the two subsystems, and the adaptive robust finite-time bioinspired neurodynamics controller (ARFBNC) is designed based on the state feedback control laws and two subsystems. The stability conditions in the form of linear matrix inequalities (LMIs) are derived by introducing the Lyapunov–Krasovskii functional. The unmeasurable angular and linear velocities, and time-varying bounded disturbance are estimated effectively by employing the state feedback control laws with observers. The smooth bounded outputs are obtained and the sharp jumps of initial values for the state variables are reduced. The closed-loop system is asymptotically stable and the state errors converge to an adjustable bounded region by introducing the Lyapunov–Krasovskii functional. The simulations are performed to show the effectiveness of the proposed methods. },
keywords = {Unmeasurable angular and linear velocities, Bounded disturbance, Subsystems, Adaptive robust finite-time controller, Bioinspired neurodynamics approach},
language = {English},
publisher = {Elsevier B.V.}
}

This paper addresses the stability analysis and adaptive robust finite-time bioinspired neurodynamics control for a class of mobile robot systems with unmeasurable angular and linear velocities, and time-varying bounded disturbance. The error system of the mobile robot is decomposed into two subsystems based on the system model. The state feedback control laws with observers are designed for the two subsystems, and the adaptive robust finite-time bioinspired neurodynamics controller (ARFBNC) is designed based on the state feedback control laws and two subsystems. The stability conditions in the form of linear matrix inequalities (LMIs) are derived by introducing the Lyapunov–Krasovskii functional. The unmeasurable angular and linear velocities, and time-varying bounded disturbance are estimated effectively by employing the state feedback control laws with observers. The smooth bounded outputs are obtained and the sharp jumps of initial values for the state variables are reduced. The closed-loop system is asymptotically stable and the state errors converge to an adjustable bounded region by introducing the Lyapunov–Krasovskii functional. The simulations are performed to show the effectiveness of the proposed methods.

@article{li_2019,
title = {Four-Direction Search Scheme of Path Planning for Mobile Agents},
author = {Li, K.; Yuan, C.; Wang, J.; Dong, X.},
journal = {Robotica},
year = {2019},
institution = {University of Rhode Island, USA; Guangxi Science and Technology Normal University, China},
abstract = {This paper presents a neural network-based four-direction search scheme of path planning for mobile agents, given a known environmental map with stationary obstacles. Firstly, the map collision energy is modeled for all the obstacles based on neural network. Secondly, for the shorted path-search purpose, the path energy is considered. Thirdly, to decrease the path-search time, a variable step-length is designed with respect to collision energy of the previous iteration path. Simulation results demonstrate that the variable step-length is effective and can decrease the iteration time substantially. Lastly, experimental results show that the mobile agent tracks the generated path well. Both the simulation and experiment results substantiate the feasibility and realizability of the presented scheme. },
keywords = {neural network, path planning, obstacles, collison energy, iteration},
language = {English},
publisher = {Cambridge University Press}
}

This paper presents a neural network-based four-direction search scheme of path planning for mobile agents, given a known environmental map with stationary obstacles. Firstly, the map collision energy is modeled for all the obstacles based on neural network. Secondly, for the shorted path-search purpose, the path energy is considered. Thirdly, to decrease the path-search time, a variable step-length is designed with respect to collision energy of the previous iteration path. Simulation results demonstrate that the variable step-length is effective and can decrease the iteration time substantially. Lastly, experimental results show that the mobile agent tracks the generated path well. Both the simulation and experiment results substantiate the feasibility and realizability of the presented scheme.

@conference{diaz-cacho_2019,
title = {Predictive distance-based Send-on-Delta in trajectory tracking under network constraints},
author = {Diaz-Cacho, M.; Falcon, P.; Delgado, E.; Lopez, J. },
booktitle = {IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society},
year = {2019},
institution = {University of Vigo, Spain},
abstract = {Send-on-Delta (SoD) transmission strategies takes decision to send a data-packet based on a relationship between the data, a reference data and a threshold called delta-value. This work presents a solution to determine dynamically the delta-value for the linear predicted Send-on-Delta strategy given a desired average throughput. The proposed solution is based on the determination of a relationship between the delta-value and the throughput, and modeling in real-time the transmission rate. The goal is to reduce the tracking error relative to the traditional periodic transmission methods. Simulation results show the feasibility of the method tested for continuous uniform signals and a robot trajectory in a cyber-physical space. },
issn = {2577-1647},
keywords = {Throughput, Trajectory, Mathematical model, Robot sensing systems, Electronic mail, Trajectory tracking},
language = {English},
publisher = {IEEE}
}

Send-on-Delta (SoD) transmission strategies takes decision to send a data-packet based on a relationship between the data, a reference data and a threshold called delta-value. This work presents a solution to determine dynamically the delta-value for the linear predicted Send-on-Delta strategy given a desired average throughput. The proposed solution is based on the determination of a relationship between the delta-value and the throughput, and modeling in real-time the transmission rate. The goal is to reduce the tracking error relative to the traditional periodic transmission methods. Simulation results show the feasibility of the method tested for continuous uniform signals and a robot trajectory in a cyber-physical space.

@conference{ushikoshi_2019,
title = {Real-Time Mamdani-type Fuzzy Maneuvering Control of a Differential-Drive Mobile Robot},
author = {De A Ushikoshi, T.; Do Nascimento, R.C.; Coutinho, P.H.; Chagas, T.P.; Schnitman, L.},
booktitle = {14th Brazilian Symposium on Intelligent Automation (SBAI 2019)},
year = {2019},
institution = {Universidade Estadual de Santa Cruz, Brazil; Universidade Federal de Minas Gerais, Brazil; Universidade Federal da Bahia, Brazil},
abstract = {This paper concerns the real-time application of Mamdani-type Fuzzy Logic Controllers (FLCs) for maneuvering trajectory tracking of a differential-drive mobile robot, the Quanser QBot 2. Based on a recent fuzzy control strategy that allows the robot to move in both forward and backward directions (FB-Controller), a new FLC with sigmoidal and pi-shaped input membership functions is proposed, the FBm-Controller. The aim of this modification is providing smoother movements during the trajectory tracking, improving real-time performance. The proposal is compared with the FB-Controller and F-Controller, where the latter only allows forward movements. Simulations and real-time experiments performed on QBot 2 robot illustrate the advantages of FBm-Controller over the two other approaches. },
keywords = {Fuzzy control, Maneuvering trajectory tracking, Differential-drive mobile robot, Dynamic modelling},
language = {English}
}

This paper concerns the real-time application of Mamdani-type Fuzzy Logic Controllers (FLCs) for maneuvering trajectory tracking of a differential-drive mobile robot, the Quanser QBot 2. Based on a recent fuzzy control strategy that allows the robot to move in both forward and backward directions (FB-Controller), a new FLC with sigmoidal and pi-shaped input membership functions is proposed, the FBm-Controller. The aim of this modification is providing smoother movements during the trajectory tracking, improving real-time performance. The proposal is compared with the FB-Controller and F-Controller, where the latter only allows forward movements. Simulations and real-time experiments performed on QBot 2 robot illustrate the advantages of FBm-Controller over the two other approaches.

@conference{yazdjerdi2_2018,
title = {Actuator Fault Tolerant Control in a Team of Mobile Robots},
author = {Yazdjerdi, P.; Meskin, N.},
booktitle = {2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)},
year = {2018},
institution = {Qatar University, Doha, Qatar},
abstract = {In this paper, a fault tolerant controller is developed for loss of effectiveness actuator faults in differential drive mobile robots. Based on the extended Kalman filter technique, a joint parameter and state estimation method is used to estimate the actuator loss of effectiveness gains as the parameters of the system. The estimated gains are then used in the controller to compensate the effect of actuator faults. Moreover, a fault tolerant leader-follower controller is developed to control multiple robots moving on a desired trajectory in a formation in the presence of actuator faults in leader or followers. The proposed method is implemented on Qbot-2 and its performance is experimentally validated. },
keywords = {Fault tolerant control (FTC), Mobile robots, Extended Kalman filter, Loss of effectiveness actuator fault, Leader-Follower},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-9583-8 }
}

In this paper, a fault tolerant controller is developed for loss of effectiveness actuator faults in differential drive mobile robots. Based on the extended Kalman filter technique, a joint parameter and state estimation method is used to estimate the actuator loss of effectiveness gains as the parameters of the system. The estimated gains are then used in the controller to compensate the effect of actuator faults. Moreover, a fault tolerant leader-follower controller is developed to control multiple robots moving on a desired trajectory in a formation in the presence of actuator faults in leader or followers. The proposed method is implemented on Qbot-2 and its performance is experimentally validated.

@article{yazdjerdi_2018,
title = {Design and real-time implementation of actuator fault-tolerant control for differential-drive mobile robots based on multiple-model approach},
author = {Yazdjerdi, P.; Meskin, N.},
journal = {Journal of Systems and Control Engineering},
year = {2018},
volume = {232},
number = {6},
institution = {Qatar University, Doha, Qatar},
abstract = {In this article, an actuator fault-tolerant control scheme is proposed for differential-drive mobile robots based on the concept of multiple-model approach. The nonlinear kinematic model of the differential-drive mobile robot is discretized and a bank of extended Kalman filters is designed to detect, isolate, and identify actuator faults. A fault-tolerant controller is then developed based on the detected fault to accommodate its effect on the trajectory-tracking performance of the mobile robot. Extensive experimental results are presented to demonstrate the efficacy of the proposed fault-tolerant control approach. },
keywords = {Multiple-model-based approach, fault-tolerant control, extended Kalman filter, differential-drive mobile robot},
language = {English},
publisher = {SAGE},
pages = {652-661}
}

In this article, an actuator fault-tolerant control scheme is proposed for differential-drive mobile robots based on the concept of multiple-model approach. The nonlinear kinematic model of the differential-drive mobile robot is discretized and a bank of extended Kalman filters is designed to detect, isolate, and identify actuator faults. A fault-tolerant controller is then developed based on the detected fault to accommodate its effect on the trajectory-tracking performance of the mobile robot. Extensive experimental results are presented to demonstrate the efficacy of the proposed fault-tolerant control approach.

@article{mu_2018,
title = {Distributed LQR Consensus Control for Heterogeneous Multi-Agent Systems: Theory and Experiments},
author = {Mu, B.; Shi, Y.},
journal = {IEEE/ASME Transactions on Mechatronics},
year = {2018},
institution = {University of Victoria, British Columbia Canada },
abstract = {Controlling heterogeneous multi-agent systems (MASs) to cooperatively accomplish tasks is currently an emerging topic in the application-oriented research of robotics. This paper investigates the consensus problem of an MAS consisting of quadrotors and two-wheeled mobile robots (2WMRs). Directed and switching interaction topologies over the network are considered. We propose a distributed linear quadratic regulation (LQR) consensus protocol for the quadrotors and design an LQR-based Rotate&Run Consensus Scheme for the 2WMRs to update the states. We use the algebraic graph theory and stochastic matrix analysis to conduct the convergence analysis of consensus. The underactuation characteristic of the 2WMR dynamics is considered in the controller design. The effectiveness of the control methods is verified by experiments. },
issn = {1941-014X },
keywords = {Consensus, multi-agent systems, two-wheeled mobile robot, quadrotor, distributed LQR},
language = {English},
publisher = {IEEE}
}

Controlling heterogeneous multi-agent systems (MASs) to cooperatively accomplish tasks is currently an emerging topic in the application-oriented research of robotics. This paper investigates the consensus problem of an MAS consisting of quadrotors and two-wheeled mobile robots (2WMRs). Directed and switching interaction topologies over the network are considered. We propose a distributed linear quadratic regulation (LQR) consensus protocol for the quadrotors and design an LQR-based Rotate&Run Consensus Scheme for the 2WMRs to update the states. We use the algebraic graph theory and stochastic matrix analysis to conduct the convergence analysis of consensus. The underactuation characteristic of the 2WMR dynamics is considered in the controller design. The effectiveness of the control methods is verified by experiments.

@article{ce_2018,
title = {Finite-Time Switched Second-Order Sliding-Mode Control of Nonholonomic Wheeled Mobile Robot Systems},
author = {Ce, H.; Hongbin, W.; Xiaoyan, C.; Zhen, Z.; Shungang, G.; Zhongquan, H.},
journal = {Complexity},
year = {2018},
volume = {2018},
institution = {Yanshan University, China},
abstract = {A continuous finite-time robust control method for the trajectory tracking control of a nonholonomic wheeled mobile robot (NWMR) is presented in this paper. The proposed approach is composed of conventional sliding-mode control (SMC) in the internal loop and modified switched second-order sliding-mode (S-SOSM) control in the external loop. Sliding-mode controller is equivalently represented as stabilization of the nominal system without uncertainties. An S-SOSM control algorithm is employed to counteract the impact of state-dependent unmodeled dynamics and time-varying external disturbances, and the unexpected chattering has been attenuated significantly. Particularly, state-space partitioning is constructed to obtain the bounds of uncertainty terms and accomplish different control objectives under different requirements. Simulation and experiment results are used to demonstrate the effectiveness and applicability of the proposed approach. },
language = {English},
publisher = {Hindawi Publishing Corp.}
}

A continuous finite-time robust control method for the trajectory tracking control of a nonholonomic wheeled mobile robot (NWMR) is presented in this paper. The proposed approach is composed of conventional sliding-mode control (SMC) in the internal loop and modified switched second-order sliding-mode (S-SOSM) control in the external loop. Sliding-mode controller is equivalently represented as stabilization of the nominal system without uncertainties. An S-SOSM control algorithm is employed to counteract the impact of state-dependent unmodeled dynamics and time-varying external disturbances, and the unexpected chattering has been attenuated significantly. Particularly, state-space partitioning is constructed to obtain the bounds of uncertainty terms and accomplish different control objectives under different requirements. Simulation and experiment results are used to demonstrate the effectiveness and applicability of the proposed approach.

@conference{priyasad_2018,
title = {Point Cloud Based Autonomous Area Exploration Algorithm},
author = {Priyasad, D.; Jayasanka, Y.; Udayanath, H.; Jayawardhana, D.; Sooriyaarachchi, S.; Gamage, C.; Kottege, N.},
booktitle = {Moratuwa Engineering Research Conference (MerCon) 2018},
year = {2018},
institution = {University of Moratuwa, Sri Lanka; Robotics and Autonomous, Systems Group, CSIRO, Australia},
abstract = {Autonomous navigation is a subject that is highly important in robotics, especially when it comes to the robotic applications in disaster management etc. While there are many algorithms to implement autonomous navigation, most of them are dependent on prior knowledge of the environment and apriori maps. While effective in some scenarios, these algorithms fail to perform when the environment has been subjected to changes that might invalidate the prior map. This paper presents a point cloud based algorithm which can be used in a situation where the prior knowledge of the environment is highly inaccurate. The proposed algorithm uses depth images to get a local map, which it expands by searching for uncharted areas picking the next best location to explore using a breadth first approach given a set of constraints. Rather than using 2D space/occupancy grid map, the proposed algorithm exploits the maps in the 3D space allowing the navigation system to perform effectively in uneven terrains and use inclined planes to its advantage. },
keywords = {Autonomous Area Exploration, Navigation Algorithm, Path Planning, Point Cloud, 3D Mapping},
language = {English}
}

Autonomous navigation is a subject that is highly important in robotics, especially when it comes to the robotic applications in disaster management etc. While there are many algorithms to implement autonomous navigation, most of them are dependent on prior knowledge of the environment and apriori maps. While effective in some scenarios, these algorithms fail to perform when the environment has been subjected to changes that might invalidate the prior map. This paper presents a point cloud based algorithm which can be used in a situation where the prior knowledge of the environment is highly inaccurate. The proposed algorithm uses depth images to get a local map, which it expands by searching for uncharted areas picking the next best location to explore using a breadth first approach given a set of constraints. Rather than using 2D space/occupancy grid map, the proposed algorithm exploits the maps in the 3D space allowing the navigation system to perform effectively in uneven terrains and use inclined planes to its advantage.

@article{wang3_2018,
title = {Simultaneous Stabilization and Tracking of Nonholonomic WMRs with Input Constraints: Controller Design and Experimental Validation},
author = {Wang, Z.; Li, G.; Chen, X.; Zhang, H.; Chen, Q.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2018},
institution = {Tongji University, China},
abstract = {Considering input constraints and parameter uncertainty of the nonholonomic WMRs, a new control law has been designed to solve the tracking and stabilization control problems simultaneously. The asymptotic convergence of the stabilization or tracking errors is achieved by the smooth controller with time-varying feedback parameters subject to set conditions. A geometric-based parameter design strategy is employed to overcome the difficulties resulted by input constraints. With the parameter design strategy, the designed parameters satisfy the set conditions and the control inputs stay in constrained domain. Experimental studies have been conducted to verify the effectiveness of the proposed control law. },
keywords = {nonholonomic system, stabilization, trajectory tracking, input constraints, system uncertainty},
language = {English},
publisher = {IEEE}
}

Considering input constraints and parameter uncertainty of the nonholonomic WMRs, a new control law has been designed to solve the tracking and stabilization control problems simultaneously. The asymptotic convergence of the stabilization or tracking errors is achieved by the smooth controller with time-varying feedback parameters subject to set conditions. A geometric-based parameter design strategy is employed to overcome the difficulties resulted by input constraints. With the parameter design strategy, the designed parameters satisfy the set conditions and the control inputs stay in constrained domain. Experimental studies have been conducted to verify the effectiveness of the proposed control law.

@conference{hamke_2018,
title = {WHY Lab: Discovering Engineering},
author = {Hamke, E.; Jordan, R.; Molki, A.; Lee, T.},
booktitle = {WEEF-GEDC 2018},
year = {2018},
institution = {University of New Mexico, USA; Quanser, Canada},
abstract = {The intention of the WHY Lab is to foster a scientific approach to acquiring knowledge by encouraging students to observe the world around them. We are proposing an Introduction to Engineering course that will lead the prospective engineering students to discover their engineering vocation based on experiments representative of the engineering applications. To instill the idea that engineering is about “doing” and not just learning “equations, heuristics and theories”. The Lab’s approach fosters a student confidence to design experiments and observe the outcomes. The new experiments become part of the catalogue of explorations. The new experiments focus on issues relevant to the student interests and keep the lab’s mission current. The internet and the pedagogy of engineering education has led to a system of accepted principles from which you could deduce an explanation for what you observed. Engineering program’s reliance on testing and homework results in codifying mathematics and scientific principles. Further, student reliance on the Internet to find facts, solutions, and generalizations, avoids the need for critical thinking or the use of an experimental approach. These factors lead to a rigid system with very little room for innovation or new thought. },
keywords = {Experiential Learning, Freshman Recruiting, Student Development, Collaboration with Education and Technology Partners, Engineering Education},
language = {English}
}

The intention of the WHY Lab is to foster a scientific approach to acquiring knowledge by encouraging students to observe the world around them. We are proposing an Introduction to Engineering course that will lead the prospective engineering students to discover their engineering vocation based on experiments representative of the engineering applications. To instill the idea that engineering is about “doing” and not just learning “equations, heuristics and theories”. The Lab’s approach fosters a student confidence to design experiments and observe the outcomes. The new experiments become part of the catalogue of explorations. The new experiments focus on issues relevant to the student interests and keep the lab’s mission current.
The internet and the pedagogy of engineering education has led to a system of accepted principles from which you could deduce an explanation for what you observed. Engineering program’s reliance on testing and homework results in codifying mathematics and scientific principles. Further, student reliance on the Internet to find facts, solutions, and generalizations, avoids the need for critical thinking or the use of an experimental approach. These factors lead to a rigid system with very little room for innovation or new thought.

@conference{fauser_2017,
title = {A comparison of inertial-based navigation algorithms for a low-cost indoor mobile robot},
author = {Fauser, T.; Bruder, S.; El-Osery, A.},
booktitle = {2017 12th International Conference on Computer Science and Education (ICCSE)},
year = {2017},
institution = {Embry-Riddle Aeronautical University, AZ, USA; New Mexico Tech, NM, USA},
abstract = {Reliable navigation of a low-cost mobile robot in an indoor environment can prove to be challenging as position fixing sensors, such as a GNSS receiver, are typically unavailable. Subscribing to the premise of a baseline of odometry and inertial sensors, this paper compares three navigation strategies, namely, a full 6-DOF inertial measurement unit (IMU) with kinematic constraints, a partial IMU with gyro pseudo-measurements, and an IMU with a depth camera. In the third configuration, by embracing the reality that vertical and horizontal planes dominate the indoor environment, an infrared depth camera is employed to determine surface normals and thereby provide attitude aiding. The paper presents a theoretical basis of the aided inertial navigational problems, MATLAB/Simulink-based simulation results, and finally the performance realized from the implementation of the algorithms on a QUANSER QBot 2 mobile robot employing a VectorNav VN-200 IMU and Kinect IR depth camera. },
issn = {2473-9464 },
keywords = {Localization, inertial navigation, inertial measurement unit, odometry, mobile robot, depth camera, aided inertial navigation},
language = {English},
publisher = {IEEE},
isbn = {978-1-5090-2509-1}
}

Reliable navigation of a low-cost mobile robot in an indoor environment can prove to be challenging as position fixing sensors, such as a GNSS receiver, are typically unavailable. Subscribing to the premise of a baseline of odometry and inertial sensors, this paper compares three navigation strategies, namely, a full 6-DOF inertial measurement unit (IMU) with kinematic constraints, a partial IMU with gyro pseudo-measurements, and an IMU with a depth camera. In the third configuration, by embracing the reality that vertical and horizontal planes dominate the indoor environment, an infrared depth camera is employed to determine surface normals and thereby provide attitude aiding. The paper presents a theoretical basis of the aided inertial navigational problems, MATLAB/Simulink-based simulation results, and finally the performance realized from the implementation of the algorithms on a QUANSER QBot 2 mobile robot employing a VectorNav VN-200 IMU and Kinect IR depth camera.

@article{wang_2017,
title = {Consensus Control for a Multi-agent System with Integral-type Event-triggering Condition and Asynchronous Periodic Detection},
author = {Wang, A.; Mu, B.; Shi, Y.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2017},
institution = {Harbin Institute of Technology, China},
abstract = {In this paper, we use an event-triggered control method to study the consensus problem for an asynchronous distributed multi-agent system. An integral-type event-triggering condition is proposed. Each agent periodically checks its triggering condition by its own clock. When the triggering condition for an agent is satisfied, then control inputs of this agent and its neighbors are updated. Based on local information, we present the consensus protocol, and using Lyapunov methods, we show that all agents asymptotically reach an agreement on states. Finally, experiments are presented to demonstrate the effectiveness of our proposed protocol. },
issn = {0278-0046},
keywords = {Multi-agent systems; asynchronous consensus control; integral-type event-triggering condition; two-wheeled mobile robot},
language = {English},
publisher = {IEEE}
}

In this paper, we use an event-triggered control method to study the consensus problem for an asynchronous distributed multi-agent system. An integral-type event-triggering condition is proposed. Each agent periodically checks its triggering condition by its own clock. When the triggering condition for an agent is satisfied, then control inputs of this agent and its neighbors are updated. Based on local information, we present the consensus protocol, and using Lyapunov methods, we show that all agents asymptotically reach an agreement on states. Finally, experiments are presented to demonstrate the effectiveness of our proposed protocol.

@article{alouache_2017,
title = {Fuzzy logic PD controller for trajectory tracking of an autonomous differential drive mobile robot (ie Quanser Qbot)},
author = {Alouache, A.; Wu, Q.},
journal = {Industrial Robot: An International Journal},
year = {2017},
volume = {45},
number = {1},
institution = {Beijing Institute of Technology, Beijing, China},
abstract = {Purpose: The aim of this paper is to propose a robust robot fuzzy logic proportional-derivative (PD) controller for trajectory tracking of autonomous nonholonomic differential drive wheeled mobile robot (WMR) of the type Quanser Qbot. Design/methodology/approach Fuzzy robot control approach is used for developing a robust fuzzy PD controller for trajectory tracking of a nonholonomic differential drive WMR. The linear/angular velocity of the differential drive mobile robot are formulated such that the tracking errors between the robot’s trajectory and the reference path converge asymptotically to zero. Here, a new controller zero-order Takagy–Sugeno trajectory tracking (ZTS-TT) controller is deduced for robot’s speed regulation based on the fuzzy PD controller. The WMR used for the experimental implementation is Quanser Qbot which has two differential drive wheels; therefore, the right/left wheel velocity of the differential wheels of the robot are worked out using inverse kinematics model. The controller is implemented using MATLAB Simulink with QUARC framework, downloaded and compiled into executable (.exe) on the robot based on the WIFI TCP/IP connection. Findings Compared to other fuzzy proportional-integral-derivative (PID) controllers, the proposed fuzzy PD controller was found to be robust, stable and consuming less resources on the robot. The comparative results of the proposed ZTS-TT controller and the conventional PD controller demonstrated clearly that the proposed ZTS-TT controller provides better tracking performances, flexibility, robustness and stability for the WMR. Practical implications The proposed fuzzy PD controller can be improved using hybrid techniques. The proposed approach can be developed for obstacle detection and collision avoidance in combination with trajectory tracking for use in environments with obstacles. Originality/value A robust fuzzy logic PD is developed and its performances are compared to the existing fuzzy PID controller. A ZTS-TT controller is deduced for trajectory tracking of an autonomous nonholonomic differential drive mobile robot (i.e. Quanser Qbot). },
issn = {0143-991X},
keywords = {Trajectory tracking, Wheeled mobile robot, Fuzzy PD controller, Quanser Qbot, Takagy – Sugeno fuzzy inference},
language = {English},
publisher = {Emerald Publishing Limited},
pages = {23-33}
}

Purpose:
The aim of this paper is to propose a robust robot fuzzy logic proportional-derivative (PD) controller for trajectory tracking of autonomous nonholonomic differential drive wheeled mobile robot (WMR) of the type Quanser Qbot.
Design/methodology/approach
Fuzzy robot control approach is used for developing a robust fuzzy PD controller for trajectory tracking of a nonholonomic differential drive WMR. The linear/angular velocity of the differential drive mobile robot are formulated such that the tracking errors between the robot’s trajectory and the reference path converge asymptotically to zero. Here, a new controller zero-order Takagy–Sugeno trajectory tracking (ZTS-TT) controller is deduced for robot’s speed regulation based on the fuzzy PD controller. The WMR used for the experimental implementation is Quanser Qbot which has two differential drive wheels; therefore, the right/left wheel velocity of the differential wheels of the robot are worked out using inverse kinematics model. The controller is implemented using MATLAB Simulink with QUARC framework, downloaded and compiled into executable (.exe) on the robot based on the WIFI TCP/IP connection.
Findings
Compared to other fuzzy proportional-integral-derivative (PID) controllers, the proposed fuzzy PD controller was found to be robust, stable and consuming less resources on the robot. The comparative results of the proposed ZTS-TT controller and the conventional PD controller demonstrated clearly that the proposed ZTS-TT controller provides better tracking performances, flexibility, robustness and stability for the WMR.
Practical implications
The proposed fuzzy PD controller can be improved using hybrid techniques. The proposed approach can be developed for obstacle detection and collision avoidance in combination with trajectory tracking for use in environments with obstacles.
Originality/value
A robust fuzzy logic PD is developed and its performances are compared to the existing fuzzy PID controller. A ZTS-TT controller is deduced for trajectory tracking of an autonomous nonholonomic differential drive mobile robot (i.e. Quanser Qbot).

@conference{obaid_2017,
title = {Real-Time Color Object Recognition and Navigation for QUARC QBOT2},
author = {Obaid, W.; Rabie, T.; Baziyad, M.},
booktitle = {2017 International Conference on Computer and Applications (ICCA)},
year = {2017},
institution = {University of Sharjah, UAE},
abstract = {QUARC QBOT2 is a ground robot manufactured by Quanser which has a combination of Mechatronics and Robotics courseware. Object detection can be done on QBOT2 by using Microsoft Kinect which is attached to the robot for vision. There are several object recognition techniques introduced which use image properties such as the ones that depend on RGB or HSV or other space properties. Other techniques are based on local binary patterns and binary sampling. Another approach is image descriptors which are based on detecting key points such as corners then matching the key points. One of the most important challenges in real-time applications is the delay. Thus, an improved technique has to be used for detection in order to achieve robustness plus accuracy in localization for the model object. In this work, an improved object recognition technique will be applied and tested on the QBOT2 and evaluated in terms of speed plus accuracy, view point, scale, rotation and illumination invariance. },
keywords = {QBOT 2, Object recognition, Real-time},
language = {English}
}

QUARC QBOT2 is a ground robot manufactured by Quanser which has a combination of Mechatronics and Robotics courseware. Object detection can be done on QBOT2 by using Microsoft Kinect which is attached to the robot for vision. There are several object recognition techniques introduced which use image properties such as the ones that depend on RGB or HSV or other space properties. Other techniques are based on local binary patterns and binary sampling. Another approach is image descriptors which are based on detecting key points such as corners then matching the key points. One of the most important challenges in real-time applications is the delay. Thus, an improved technique has to be used for detection in order to achieve robustness plus accuracy in localization for the model object. In this work, an improved object recognition technique will be applied and tested on the QBOT2 and evaluated in terms of speed plus accuracy, view point, scale, rotation and illumination invariance.

@article{liu_2017,
title = {Target tracking control and semi-physical simulation of Qball-X4 quad-rotor unmanned aerial vehicle},
author = {Liu, L.; Pan, F.; An, Z.; Xue, D,},
journal = {International Journal of Advanced Robotic Systems},
year = {2017},
month = {-1},
institution = {Department of Information Science and Engineering, Northeastern University, Shenyang, China},
abstract = {In this article, a set of integrated ground target tracking flight system has been proposed based on the Qball-X4 quad-rotor unmanned aerial vehicle hardware platform and the QuaRC software platform. Both of the hardware and software platforms are developed by Quanser Company, Canada. The proposed tracking and positioning algorithm could be divided into several stages. First, a tracker is developed based on an optical flow method to track the target; and then, in order to improve the reliability of tracking algorithm and also help in retrieving the lost target, a cascade target detector is developed; meanwhile, a model updated scheme aiming at some possible errors in tracking and detecting process is presented based on Positive-Negative (P-N) learning system; at last, a monocular visual positioning system is designed based on the corresponding navigation message. In addition, the effectiveness of the proposed flight control system is verified by both simulation and hardware-in-loop system results in several tracking flight tests. },
keywords = {Target tracking, semi-physical simulation, Qball-X4, unmanned aerial vehicle},
language = {English},
publisher = {SAGE}
}

In this article, a set of integrated ground target tracking flight system has been proposed based on the Qball-X4 quad-rotor unmanned aerial vehicle hardware platform and the QuaRC software platform. Both of the hardware and software platforms are developed by Quanser Company, Canada. The proposed tracking and positioning algorithm could be divided into several stages. First, a tracker is developed based on an optical flow method to track the target; and then, in order to improve the reliability of tracking algorithm and also help in retrieving the lost target, a cascade target detector is developed; meanwhile, a model updated scheme aiming at some possible errors in tracking and detecting process is presented based on Positive-Negative (P-N) learning system; at last, a monocular visual positioning system is designed based on the corresponding navigation message. In addition, the effectiveness of the proposed flight control system is verified by both simulation and hardware-in-loop system results in several tracking flight tests.

@article{rabie_2017,
title = {Training-less color object recognition for autonomous robotics},
author = {Rabie, T.},
journal = {Information Sciences},
year = {2017},
volume = {418},
institution = {Department of Electrical and Computer Engineering, University of Sharjah, U.A.E},
abstract = {This paper looks at the challenge of object recognition from the perspective of achieving the final goals of practical real-world autonomous robot-vision applications; that of identifying a target of interest in the robot’s field of view and properly localizing its position in preparation for the higher-level goal of tracking and navigation. A unified framework is introduced that combines a multidimensional feature histogram approach with a multiscale pyramid approach for training-less color object recognition and localization, with direct application to autonomous robotic agents. This framework addresses the high computational cost associated with multidimensional processing by deriving the Multidimensional “Laplacian Feature Histogram Pyramid”, a novel approach to a unified multidimensional-multiscale histogram representation. Furthermore, a Taylor series formulation is employed to combine the multiscale levels of the multidimensional Laplacian feature histogram pyramid into one efficient multidimensional-multiscale “Laplacian-Taylor Feature Histogram” for rapid object recognition and localization. The paper describes the criteria for target detection and localization by autonomous robots and how this newly developed framework fits these needs. Comparative results demonstrate the robustness of this recognition framework to noise and localization of target objects in cluttered scenes. },
keywords = {Multidimensional-Multiscale, Feature-histograms, Laplacian feature, Histogram pyramid, Histogram Taylor series, Reduced complexity, Multidimensional indexing, Training-less object recognition},
language = {English},
publisher = {Elsevier Inc.},
pages = {218-241}
}

This paper looks at the challenge of object recognition from the perspective of achieving the final goals of practical real-world autonomous robot-vision applications; that of identifying a target of interest in the robot’s field of view and properly localizing its position in preparation for the higher-level goal of tracking and navigation. A unified framework is introduced that combines a multidimensional feature histogram approach with a multiscale pyramid approach for training-less color object recognition and localization, with direct application to autonomous robotic agents. This framework addresses the high computational cost associated with multidimensional processing by deriving the Multidimensional “Laplacian Feature Histogram Pyramid”, a novel approach to a unified multidimensional-multiscale histogram representation. Furthermore, a Taylor series formulation is employed to combine the multiscale levels of the multidimensional Laplacian feature histogram pyramid into one efficient multidimensional-multiscale “Laplacian-Taylor Feature Histogram” for rapid object recognition and localization. The paper describes the criteria for target detection and localization by autonomous robots and how this newly developed framework fits these needs. Comparative results demonstrate the robustness of this recognition framework to noise and localization of target objects in cluttered scenes.

@conference{peterson_2016,
title = {Application of Active-Passive Dynamic Consensus Filter Approach to Multitarget Tracking Problem for Situational Awareness in Unknown Environments},
booktitle = {AIAA Guidance, Navigation, and Control Conference 2016},
year = {2016},
institution = {Mechanical and Aerospace Engineering Department,Missouri University of Science and Technology, MO, USA},
abstract = {In this paper, we present an application of multiagent systems to the multitarget tracking problem, where networked nodes exchange their local information to construct a global map of an unknown environment for situational awareness. Recognizing the fact that networked nodes can be heterogeneous with respect to the number of targets sensed in their respective local environments, we utilize a recently developed active{passive dynamic consensus lters approach (Refs. 1, 2). Specically, a node is considered active for targets it is able to sense and passive for targets it is unable to sense. We use two ground robots equipped with object detection sensors to track local targets in a global frame. Networked nodes use the active{passive dynamic consensus lters approach to distribute and fuse information to make all networked nodes aware of all targets in the environment. },
language = {English},
publisher = {AIAA}
}

In this paper, we present an application of multiagent systems to the multitarget tracking problem, where networked nodes exchange their local information to construct a global map of an unknown environment for situational awareness. Recognizing the fact that networked nodes can be heterogeneous with respect to the number of targets sensed in their respective local environments, we utilize a recently developed active{passive dynamic consensus lters approach (Refs. 1, 2). Specically, a node is considered active for targets it is able to sense and passive for targets it is unable to sense. We use two ground robots equipped with object detection sensors to track local targets in a global frame. Networked nodes use the active{passive dynamic consensus lters approach to distribute and fuse information to make all networked nodes aware of all targets in the environment.

@article{mu_2016,
title = {Design and Implementation of Non-uniform Sampling Cooperative Control on a Group of Two-wheeled Mobile Robots},
author = {Mu, B.; Chen, J.; Shi, Y.; Chang, Y.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2016},
abstract = {This paper investigates the consensus prob- lem for a group of two-wheeled mobile robots (2WMRs) using non-uniform sampling. The directed and switching communication topologies are considered. The control pro- tocols for the first-order/second-order system dynamics are designed with bounded control gains. The Rotate &Run Scheme is proposed to update the vehiclesÍ states: 1) The vehicle calculates its goal orientation and the input of each wheel at the sampling time instants by using the states of itself and the neighbors; 2) the vehicle rotates in place until it aims at the calculated direction; 3) the vehicle moves for- ward/backward with the calculated wheel velocities until the next sampling time instant. It is shown that consensus in a group of 2WMRs can be achieved when the switching di- rected graphs satisfy certain conditions. The convergence analysis of consensus is conducted based on algebraic graph theory and stochastic matrix analysis. Experiments demonstrate the effectiveness of the proposed methods. },
issn = {0278-0046},
keywords = {Consensus, multi-agent systems, two- wheeled mobile robot, non-uniform sampling},
language = {English},
publisher = {IEEE}
}

This paper investigates the consensus prob- lem for a group of two-wheeled mobile robots (2WMRs) using non-uniform sampling. The directed and switching communication topologies are considered. The control pro- tocols for the first-order/second-order system dynamics are designed with bounded control gains. The Rotate &Run Scheme is proposed to update the vehiclesÍ states: 1) The vehicle calculates its goal orientation and the input of each wheel at the sampling time instants by using the states of itself and the neighbors; 2) the vehicle rotates in place until it aims at the calculated direction; 3) the vehicle moves for- ward/backward with the calculated wheel velocities until the next sampling time instant. It is shown that consensus in a group of 2WMRs can be achieved when the switching di- rected graphs satisfy certain conditions. The convergence analysis of consensus is conducted based on algebraic graph theory and stochastic matrix analysis. Experiments demonstrate the effectiveness of the proposed methods.

@conference{kamel_2013_2,
title = {Real-Time Optimal Formation Reconfiguration of Multiple Wheeled Mobile Robots Based on Particle Swarm Optimization},
author = {Kamel, M.A.; Yu, X.; Zhang, Y.},
booktitle = {2016 12th World Congress on Intelligent Control and Automation (WCICA)},
year = {2016},
institution = {Department of Mechanical and Industrial Engineering, Concordia University, Canada},
abstract = {This paper investigates optimal formation reconfiguration of multiple wheeled mobile robots (WMRs). The idea is to convert the reconfiguration problem as an optimization problem, while the objective is to minimize the time to achieve the desired formation reconfiguration within the constraints of the robotsÍ dynamics and collision avoidance. A hybrid approach of control parametrization and time discretization (CPTD) and particle swarm optimization (PSO) is proposed to solve this problem. Since PSO cannot solve the continuous control inputs, CPTD is adopted to give an approximate piecewise linearization of the control inputs to substitute the continuous control inputs while PSO is used to find the global optimum solution. Experimental results demonstrate the effectiveness of the proposed algorithm. },
language = {English},
publisher = {IEEE},
pages = {703-708}
}

This paper investigates optimal formation reconfiguration of multiple wheeled mobile robots (WMRs). The idea is to convert the reconfiguration problem as an optimization problem, while the objective is to minimize the time to achieve the desired formation reconfiguration within the constraints of the robotsÍ dynamics and collision avoidance. A hybrid approach of control parametrization and time discretization (CPTD) and particle swarm optimization (PSO) is proposed to solve this problem. Since PSO cannot solve the continuous control inputs, CPTD is adopted to give an approximate piecewise linearization of the control inputs to substitute the continuous control inputs while PSO is used to find the global optimum solution. Experimental results demonstrate the effectiveness of the proposed algorithm.

@conference{mija_2016,
title = {Robust controller for trajectory tracking of a Mobile Robot},
author = {Navin Chandra, P.; Mija, S.},
booktitle = {IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES)},
year = {2016},
institution = {National Institute of Technology Calicut, India},
abstract = {Mobile Robots are robots that can move from one place to another autonomously, ie. without external human assistance. Proper control methods are to be used for autonomously controlling the motion of these robots. As these robots are to be utilized in real-world situations, the controller used should be promising and robust in nature. In this paper, the tracking control of a Non-holonomous Differential Drive Wheeled Mobile Robot using robust Sliding Mode Control is presented. The model of the mobile robot, QBot 2, by Quanser, is utilized for checking the validity of the controller. },
keywords = {Wheeled Mobile Robot; Sliding Mode Control; Trajectory Tracking},
language = {English},
publisher = {IEEE},
isbn = {978-1-4673-8588-6 }
}

Mobile Robots are robots that can move from one place to another autonomously, ie. without external human assistance. Proper control methods are to be used for autonomously controlling the motion of these robots. As these robots are to be utilized in real-world situations, the controller used should be promising and robust in nature. In this paper, the tracking control of a Non-holonomous Differential Drive Wheeled Mobile Robot using robust Sliding Mode Control is presented. The model of the mobile robot, QBot 2, by Quanser, is utilized for checking the validity of the controller.

@article{taskiran_2016,
title = {Wi-Fi Control of Mobile Robot Motion Types Based on Differential Drive Kinematics Modelling Approach},
author = {Taskiran, E.; Durna, Y.; Kocer, H.},
journal = {International Journal of Applied Mathematics, Electronics and Computers},
year = {2016},
volume = {4},
abstract = {Recently, utilization of mobile robots has increased substantially. Accordingly, wireless communication is preferred in mobil e robots. QBot 2 is an autonomous ground robot which is a new product of Quarc. The QBot 2 utilizes an onboard data acqui sition card and a wireless embedded computer to measure the onboard sensors and drive motors. In this study, QBot 2 mobile robot is evalu ated in terms of its ability to maneuver. In this way, controlling QBot 2 mobile robot in real time is planned while a command recognition syste m is developed. Connection with the QBot 2 is carried out in a wireless environment. A Simulink model is developed in MATLAB¬ environment. The created model is built with Quarc control software. Compiled model is downloaded with TC P/IP connection to QBot 2 and the application is carried out on an embedded computer. The QBot 2 mobile platform consists of two c entral drive wheels mounted on a common axis. This drive configuration is known as differential drive. The two drive wheels ar e independently driven forward and backward in order to actuate the robot. Motion of the wheels is realized using high performance DC motors. When the results are analyzed, 13 different motion types are observed in total. The observed motion types could be used as references in future works since many practical applications, such as the remote control of QBot 2 mobile robot via the human voice, require the a vailability of different motion types. },
keywords = {Intelligent robotic systems,Mobile robots,Wi-Fi based remote control.},
language = {English},
pages = {170-173}
}

Recently, utilization of mobile robots has increased substantially. Accordingly, wireless communication is preferred in mobil e robots. QBot 2 is an autonomous ground robot which is a new product of Quarc. The QBot 2 utilizes an onboard data acqui sition card and a wireless embedded computer to measure the onboard sensors and drive motors. In this study, QBot 2 mobile robot is evalu ated in terms of its ability to maneuver. In this way, controlling QBot 2 mobile robot in real time is planned while a command recognition syste m is developed. Connection with the QBot 2 is carried out in a wireless environment. A Simulink model is developed in MATLAB¬ environment. The created model is built with Quarc control software. Compiled model is downloaded with TC P/IP connection to QBot 2 and the application is carried out on an embedded computer. The QBot 2 mobile platform consists of two c entral drive wheels mounted on a common axis. This drive configuration is known as differential drive. The two drive wheels ar e independently driven forward and backward in order to actuate the robot. Motion of the wheels is realized using high performance DC motors. When the results are analyzed, 13 different motion types are observed in total. The observed motion types could be used as references in future works since many practical applications, such as the remote control of QBot 2 mobile robot via the human voice, require the a vailability of different motion types.

@inproceedings{luo_2015,
title = {A Leader-following Formation Control of Multiple Mobile Robots with Obstacle},
author = {Luo, Jing; Liu, Cheng-Lin; Liu, Fei},
booktitle = {Proceeding of the 2015 IEEE International Conference on Information and Automation},
year = {2015},
institution = {Jiangnan University, China},
abstract = {By combining the Polar Histogram obstacle avoidance method, a leader-follower coordination formation control algorithm is proposed to solve the formation control problem of multiple mobile robots. Based on the formation control in leader-follower structure, a virtual-follower robot is introduced, and the formation control problem can be regarded as the follower robots tracking the virtual-follower robot. With the sensor technology, the corresponding path for robot movement strategy is provided in a simple or complicated environment so as to achieve the purpose of real-time navigation. With two-wheel differential robot Qbot as the investigation object, semi-physical simulation platform is built for simulation experiments. The simulation results show that the method can effectively achieve the coordination formation and obstacle avoidance control of multi-robot system. },
keywords = {multiple mobile robots, leader-follower formation, obstacle avoidance},
language = {English},
publisher = {IEEE},
pages = {2153 - 2158}
}

By combining the Polar Histogram obstacle avoidance method, a leader-follower coordination formation control algorithm is proposed to solve the formation control problem of multiple mobile robots. Based on the formation control in leader-follower structure, a virtual-follower robot is introduced, and the formation control problem can be regarded as the follower robots tracking the virtual-follower robot. With the sensor technology, the corresponding path for robot movement strategy is provided in a simple or complicated environment so as to achieve the purpose of real-time navigation. With two-wheel differential robot Qbot as the investigation object, semi-physical simulation platform is built for simulation experiments. The simulation results show that the method can effectively achieve the coordination formation and obstacle avoidance control of multi-robot system.

The work presents a stand for researching mobile robots, allowing for prototyping of new or improving the existing control algorithms. The
elements of the research stand were described, including the parameters of the QBot 2e wheeled mobile robot. In addition, the article presents the
results of exemplary odometry measurements obtained for two robot paths based on data read from an inertial measurements unit equipped with a
gyroscope and an accelerometer.