This paper presents a novel method for the calibration of a parallel robot, which allows a more accurate configuration instead of a configuration based on nominal parameters. It is used, as the main sensor with one camera installed in the robot hand that determines the relative position of the robot with respect to a spherical object fixed in the working area of the robot. The positions of the end effector are related to the incremental positions of resolvers of the robot motors. A kinematic model of the robot is used to find a new group of parameters, which minimizes errors in the kinematic equations. Additionally, properties of the spherical object and intrinsic camera parameters are utilized to model the projection of the object in the image and thereby improve spatial measurements. Finally, several working tests, static and tracking tests are executed in order to verify how the robotic system behaviour improves by using calibrated parameters against nominal parameters. In order to emphasize that, this proposed new method uses neither external nor expensive sensor. That is why new robots are useful in teaching and research activities.
In this paper a visual servoing architecture based on a parallel robot for the tracking of faster moving objects with unknown trajectories is proposed. The control strategy is based on the prediction of the future position and velocity of the moving object. The synthesis of the predictive control law is based on the compensation of the delay introduced by the vision system. Demonstrating by experiments, the high-speed parallel robot system has good performance in the implementation of visual control strategies with high temporary requirements. The mechanical structure of RoboTenis System is inspired by the DELTA robot [1]. The choice of the robot is a consequence of the high requirements on the performance of the system with regard to velocity and acceleration. The kinematic analysis and the optimal design of the RoboTenis System have been presented by Angel, et al. [2]. The structure of the robot has been optimized from the view of both kinematics and dynamics respectively. The design method solves two difficulties: determining the dimensions of the parallel robot and selecting the actuators. In addition, the vision system and the control hardware have been also selected. The dynamic analysis and the preliminary control of the parallel robot
This paper describes the visual control of a parallel in order to response to future works. Typically the parallel robot called "RoboTenis". The system has been designed and mechanisms possess the advantages of high stiffness, low built in order to carry out tasks in three dimensions and inertia and large payload capacity; however, the principal dynamical environments, thus the system is capable to interact weakness is the small useful workspace and design with objects which move up to tm/s. The control strategy is difficulties. As shown is fig. 1, mechanical structure of composed by two intertwined control loops: The internal loop is RoboTenis system is inspired in DELTA robot [4].faster and considers the information from the joins, its sample Kinematical model, Jacobian matrix and the optimized model time is 0.5 ms. Second loop represents the visual servoing system which is external loop to the first mentioned, second loop of the RoboTenis system have been presented in other represents the study purpose, that it is based in the prediction of previous woks [5]. Dynamical analysis and the joint the object velocity which is obtained form visual information controller have been presented in [6] and [7]. The dynamical and its sample time is 8.3 ms. Lyapunov stability analysis, system model is based upon Lagrangian multipliers thus, is possible delays and saturation components has been taken into account.to use forearms of non-negligible inertias in the development of control strategies. Two control loops are incorporated in Keywords -Parallel robot, visual control strategies, tracking, the system: the joint loop is a control signal calculated each system stability. 0.5 ms, at this point dynamical model, kinematical model and PD action are retrofitted. The other loop is considered external since is calculated each 8.33 ms; this loop uses the
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