A Novel Point-to-Point Trajectory Planning Algorithm for Industrial Robots Based on a Locally Asymmetrical Jerk Motion Profile

摘要

Suitable trajectories with minimum execution time are essential for an industrial robot to enhance productivity in pick and place operations. A novel point-to-point trajectory planning algorithm (PTPA) is proposed to improve the motion efficiency of industrial robots. The jerk profile for a trajectory model is determined by five intervals and the jerk constraint. According to the kinematic constraints and two shape coefficients, a velocity threshold and three displacement thresholds are calculated for an individual joint to transfer the proposed jerk motion profile into four specific profiles. The optimal trajectory model of the joint is developed for the minimum-time and jerk-continuous trajectory via the performance evaluation with the input displacement and three displacement thresholds. Moreover, time-based motion synchronization for all joints is taken into account in PTPA to decrease unnecessary burdens on the actuators. The simulations illustrate that the execution time by PTPA is more efficient than that by other techniques. The experiments of a point-to-point application on a real six-axis industrial robot show that the absolute errors at the end of the motion for all joints are within 0.04°. These results prove that PTPA can be an effective point-to-point trajectory planner for industrial robots