机器人最优时间轨迹生成,就是所谓TOPP(Time Optimal Path Parametrization)问题,一般内容是满足若干约束下,尽可能快的执行完一个给定空间路径。是有两个流派的“标准”解法的。分别是数值积分方法和凸优化方法。数值积分法的论文我看到也有别的回答推荐了,不过不是最新的work。
两类方法,前者特点是计算很快,后者特点是可以在objective加入除时间以外其他preference,只要保持convex即可。具体的我不赘述了,看下面的推荐论文吧,里面都有:
Numeric Integration:
[1] A New Approach to Time-Optimal Path Parameterization based on Reachability Analysis, Hung Pham, Quang-Cuong Pham
[2] A General, Fast, and Robust Implementation of the Time-Optimal Path Parameterization Algorithm, Quang-Cuong Pham
[3] Essential Properties of Numerical Integration for Time-optimal Trajectory Planning Along a Specified Path
Convex Optimization:
[4] Time-Optimal Path Tracking for Robots: A Convex Optimization Approach, Diederik Verscheure et al.