Time-optimal trajectory planning for industrial robots based on iterative bisection selection algorithm

This paper addresses the Time-Optimal Trajectory Planning problem for industrial robots by proposing an improved algorithm based on Iterative Bisection Selection (IBS), which aims to resolve the inefficiency in traditional Bisection Algorithm (BA) caused by infeasible regions. A dynamic model of a six-axis industrial robot is established, and the parameters of the robot's dynamic model are obtained through identification experiments. Then, by combining the path parameterization method, the trajectory planning problem is transformed into a two-dimensional optimization problem. The IBS algorithm iteratively finds feasible speeds through the binary method, effectively avoiding infeasible regions while retaining the low complexity characteristic of the BA algorithm. Simulation experiments show that, compared with the BA algorithm, the IBS algorithm can generate better speed curves in circular trajectory planning.