通过逆最优控制预测机器人目标，提升无通信机器人的避障效率。
Trajectory Planning for Non-Communicating Mobile Robots using Inverse Optimal Control
- 用逆最优控制推断其他机器人目标位置
- 仿真中平均提前9.8%完成任务
- 适合多机器人协同避障场景
为实现无通信移动机器人在避障场景中的高效协作，本文提出一种结合轨迹规划与预测的新算法。通过逆最优控制方法，基于观测到的过去轨迹估计所有机器人的未知目标状态。每台机器人同时以其他机器人的视角进行自我预测，并利用估计的目标状态求解联合预测问题。最终将预测结果用于轨迹规划。2至8台机器人的仿真结果显示，相比基于恒定加速度估计目标状态的规划方法，本方法使所有车辆到达目标的中位时间缩短9.8%。此外，该方法始终能求解规划或预测问题，不会出现无解情况。
原文摘要 · Abstract (English)
To enable an efficient interaction of non-communicating mobile robots in collision avoidance scenarios, we present a novel combined trajectory planning and prediction algorithm. Inverse optimal control is used to estimate unknown goal states of all robots based on observed past trajectories. Each robot also takes the perspective of other robots in considering self-prediction and solves a joint prediction problem using the estimated goal states. The resulting predictions are then considered for planning. Simulation results of scenarios with 2-8 robots show that the median of the durations until all vehicles reach their goals is 9.8 % faster compared to planning with constant acceleration based estimated goal states. Moreover, the proposed approach never leads to the solver being unable to find a solution to the planning or prediction problem.
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