In this paper, a new mobile cable-driven parallel robot is proposed by mounting a spatial cable robot on a wheeled mobile robot. This system includes all the advantages of cable robots such as high ratio of payload to weight and good stiffness and accuracy while its deficiency of limited workspace is eliminated by the aid of its mobile chassis. The combined system covers a vast workspace area whereas it has negligible vibrations and cable sag due to using shorter cables. The dynamic equations are derived using Gibbs–Appell formulation considering viscoelasticity of the cables. Therefore, the more realistic viscoelastic cable model of the robot reveals the system flexibility effect and shows the requirements needed to control the end-effector in the conditions with cable elasticity. The viscoelastic system stability is investigated based on the input–output feedback linearization and using only the actuators feedback data. Feedback linearization controller is equipped by two additional controllers, that is, the optimal controller based on Linear Quadratic Regulator (LQR) method and finite horizon model predictive approach. They are used to control the system compromising between the control effort and error signals of the feedback linearized system. The applied control input to the robot plant is the voltage signal limited to a specified band. The validity of modeling and the designed controller efficiency are investigated using MATLAB simulation and its verification is accomplished by experimental tests conducted on the manufactured cable robot, ICaSbot.

In this paper, the feedback linearization approach is used to introduce a motion controller for unicycle-type wheeled mobile robots (UWMRs). The output function is defined as a linear combination of the error state. The novel scheme is firstly tested in numerical simulation and compared with its corresponding experimental result. Three controllers are taken from the literature and compared to the proposed approach by means of experiments. The gains of the experimentally tested controllers are selected to obtain identical energy consumption. The Optitrack commercial vision system and Pioneer P3-DX UWMR are used in real-time experimental tests. In addition, two sets of experimental results for different motion tasks are provided. The results show that the proposed controller presents the best tracking accuracy.

Optimal path planning of a closed loop cable robot, between two predefined points in presence of obstacles is the goal of this paper. This target is met by proposing a new method of optimal regulation for non linear systems while Dynamic Load Carrying Capacity (DLCC) of the robot is supposed as the related cost function. Feedback linearization is used to linearize the system while Linear Quadratic Regulator (LQR) is employed to optimize the DLCC of the system based on torque and error constraints. Obstacle avoidance for both the end-effector and cables is also considered by the aid of designing an adaptive local obstacle avoidance controller. As a result of linearized nature of the proposed optimal regulation and obstacle avoidance, fast calculation for real time applications is possible. Therefore, formulation of the optimal feedback linearization, together with calculating the DLCC of the robot based on the presented constraints is derived. Finally, a simulation study is performed to study the optimal dynamics and also the maximum DLCC of the cable robot in presence of obstacles. Simulation results are eventually compared with experimental tests conducted on IUST Cable Suspended Robot (ICaSbot) to verify the validity and efficiency of the proposed optimal controllers.

This paper presents the results of a study on the dynamical modeling, analysis, and control of a spherical rolling robot. The rolling mechanism consists of a 2-DOF pendulum located inside a spherical shell with freedom to rotate about the transverse and longitudinal axis. The kinematics of the model has been investigated through the classical methods with rotation matrices. Dynamic modeling of the system is based on the Euler–Lagrange formalism. Nonholonomic and highly nonlinear equations of motion have then been decomposed into two simpler subsystems through the decoupled dynamics approach. A feedback linearization loop with fuzzy controllers has been designed for the control of the decoupled dynamics. Rolling of the controlled mechanism over linear and curvilinear trajectories has been simulated by using the proposed decoupled dynamical model and feedback controllers. Analysis of radius of curvature over curvilinear trajectories has also been investigated.

Maximum load carrying capacity (MLCC) of flexible robot manipulators is computed based on closed-loop approach. In open-loop approach, controller is not considered, so the end effector deviation from the predefined path is significant and the accuracy constraint restrains the maximum payload before actuators go into saturation mode. In order to improve the MLCC, a method based on closed-loop strategy is presented. Since in this case the accuracy is improved the actuators constraint is not a major concern and full power of actuators can be used. Since controller can play an important role in improving the maximum payload, a sliding mode based partial feedback linearization controller is designed. Furthermore, a fuzzy variable layer is used in sliding mode design to boost the performance of the controller. However, the control strategy required measurements of elastic variables velocity that are not conveniently measurable. So a nonlinear observer is designed to estimate these variables. Stability analysis of the proposed controller and state observer are performed on the basis of Lyapunov's direct method. In order to verify the effectiveness of the presented method, simulation is done for a two-link flexible manipulator. The obtained maximum payload in open-loop and closed-loop cases is compared and the superiority of the method is illustrated and the results are discussed.

This paper presents a polar-space kinematics control method to achieve simultaneous tracking and stabilization for an omnidirectional wheeled mobile robot with three independent driving omnidirectional wheels equally spaced at 120° from one another. The kinematic model of the robot in polar coordinates is presented. With the kinematic model, a kinematic control method based on feedback linearization is proposed in order to achieve simultaneous tracking and stabilization. The proposed method is easily extended to address the path following problem. Computer simulations and experimental results are presented to show the effectiveness and usefulness of the proposed control method at slow speeds.