Minimum-Time Trajectory Planning and Control of a Pick-and-Place Five-Bar Parallel Robot

Abstract

This paper presents trajectory planning optimization and real-time control of a special five-bar parallel robot. Planning is based on a cubic spline stochastic approach that minimizes trajectory time and selects the best combination of working mode regions to circumvent all parallel singularities, allowing the size of the workspace to be increased. Identification of the dynamic model of the robot and its actuators allows a precise implementation of the trajectory planning and real-time control approach. The optimization algorithm achieves a fast trajectory and a controller that operates with an error of less than 0.7° for both actuated joints of the robot.