全动力学约束的机器人高效时间最优轨迹规划

High-efficiency Time-Optimal Trajectory Planning for Robots under Complete Dynamic Constraints

针对当前机器人时间最优轨迹规划算法存在的求解效率低、约束不完整等局限性,提出了一种改进的基于可达性分析的时间最优轨迹规划算法.该算法基于路径离散化将整个规划问题转化为多阶段迭代求值问题,求解效率高;由于考虑了包含摩擦在内的全动力学约束以及运动学约束,算法求得的结果在保证时间最优的前提下更为符合机器人实际运动性能.数值仿真实验证实了本算法的可行性和求解高效性.

Aiming at the limitations of current time-optimal trajectory planning algorithms for robots,such as low solution efficiency and incomplete constraints,we propose an improved time-optimal trajectory planning algorithm based on reachability analysis.Based on path discretization,the algorithm transforms the entire planning problem into a multi-stage iterative evaluation problem and efficiently executes it.The results of the algorithm are in line with the actual motion performance of robots under the promise of ensuring the time-optimal characteristic as a result of taking complete dynamics constraints,including friction and kinematic constraints,into account.Numerical simulation experiments confirm the feasibility and efficiency of the algorithm.