Time-Jerk optimal Trajectory Planning of Industrial Robots Based on a Hybrid WOA-GA Algorithm

An optimal and smooth trajectory for industrial robots has a positive impact on reducing the execution time in an operation vibration their joints. In this paper, methodology time-optimal jerk-continuous planning of is proposed. The entire interpolated joint space utilizing fifth-order B-splines then optimized by hybrid whale optimization algorithm genetic (WOA-GA). Two objective functions, including integral squared jerk along total time, are minimized to obtain trajectory. A B-spline interpolation technique enables achievement trajectory, while respecting kinematic limits jerk, acceleration velocity. WOA-GA utilized solve time-jerk problem with nonlinear constraints. proposed yielded good results achieved better under constraints compared algorithm, improved particle swarm adaptive cuckoo search algorithm. numerical show competent performances generate trajectories high curves short time.