多机器人协同运动中，通过调节各机器人路径执行时间，实现无碰撞、动态可行的最短工期。
Collision-free time-optimal path parameterization for multi-robot teams
- 基于优先级队列构建时空图，动态规划机器人执行顺序。
- 相比现有方法，任务完成时间减少10%-20%。
- 适用于需要高效率协同的复杂环境机器人系统。
在杂乱环境中协调多机器人运动仍是计算挑战。本文研究如何通过一组具有状态依赖执行约束的机器人，最小化其几何路径的执行时间。针对多个类汽车机器人，提出一种时间最优路径参数化（TOPP）算法，通过调节每台机器人在其路径上的执行时间，确保无碰撞且满足动态可行性。该方法利用优先级队列确定每个机器人的轨迹执行顺序，并在时空图中考虑与高优先级机器人所有可能的碰撞。实验显示，相较现有先进方法，任务完成时间（makespan）减少10%-20%，并通过仿真和硬件实验验证了方法的有效性。
原文摘要 · Abstract (English)
Coordinating the motion of multiple robots in cluttered environments remains a computationally challenging task. We study the problem of minimizing the execution time of a set of geometric paths by a team of robots with state-dependent actuation constraints. We propose a Time-Optimal Path Parameterization (TOPP) algorithm for multiple car-like agents, where the modulation of the timing of every robot along its assigned path is employed to ensure collision avoidance and dynamic feasibility. This is achieved through the use of a priority queue to determine the order of trajectory execution for each robot while taking into account all possible collisions with higher priority robots in a spatiotemporal graph. We show a 10-20% reduction in makespan against existing state-of-the-art methods and validate our approach through simulations and hardware experiments.
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