This paper presents in detail how to model, identify, and control a 3-DOF prismatics-revolute-spherical parallel manipulator in terms of relevant parameters. A reduced model based on a set of relevant parameters is obtained following a novel approach that considers a simplified dynamic model with a physically feasible set of parameters. The proposed control system is compared with the response of a model-based control that considers the complete identification of the rigid-body dynamic parameters, friction at joints, and the inertia of the actuators. The control systems are implemented on a virtual and an actual prototype. The results show that the control scheme based on the reduced model improves the trajectory tracking precision when comparing with the control scheme based on the complete set of dynamic parameters. Moreover, the reduced model shows a significant reduction in the computational burden, allowing real-time control.

This work describes Internet functions that include video file generation and real-time control as MWS (MATLAB Web server) features, which are useful for undergraduate courses. With these functions, using virtual processes, which in turn allow video animations of simulated processes, can enhance virtual laboratories. Furthermore, MWS allows the implementation of remote laboratories operating in batch mode. WinCom or any other suitable software can be used to implement online laboratories. These methodologies provide a straightforward approach for the developer of the teaching material, the control engineering lecturer, and a low-cost option for the student user.

SUMMARY: This paper presents the design, kinematics, dynamics and control of a low-cost parallel rehabilitation robot developed at the Universitat Politècnica de Valencia. Several position and force controllers have been tested to ensure accurate tracking performances. An orthopedic boot, equipped with a force sensor, has been placed over the platform of the parallel robot to perform exercises for injured ankles. Passive, active-assistive and active-resistive exercises have been implemented to train dorsi/plantar flexion, inversion and eversion ankle movements. In order to implement the controllers, the component-based middleware Orocos has been used with the advantage over other solutions that the whole scheme control can be implemented modularly. These modules are independent and can be configured and reconfigured in both configuration and runtime. This means that no specific knowledge is needed by medical staff, for example, to carry out rehabilitation exercises using this low-cost parallel robot. The integration between Orocos and ROS, with a CAD model displaying the actual position of the rehabilitation robot in real time, makes it possible to develop a teleoperation application. In addition, a teleoperated rehabilitation exercise can be performed by a specialist using a Wiimote (or any other Bluetooth device).

This paper presents a local sensor fusion technique with an event-based global position correction to improve the localization of a mobile robot with limited computational resources. The proposed algorithms use a modified Kalman filter and a new local dynamic model of an Ackermann steering mobile robot. It has a similar performance but faster execution when compared to more complex fusion schemes, allowing its implementation inside the robot. As a global sensor, an event-based position correction is implemented using the Kalman filter error covariance and the position measurement obtained from a zenithal camera. The solution is tested during a long walk with different trajectories using a LEGO Mindstorm NXT robot.