This paper presents a solution for the problem of optimal planning for a robot in a collaborative human-robot team, where the human supervisor is intermittently available to assist the robot in completing tasks more quickly. Specifically, we address the challenge of computing the fastest path between two configurations in an environment with time constraints on how long the robot can wait for assistance. To solve this problem, we propose a novel approach that utilizes the concepts of budget and critical departure times, which enables us to obtain optimal solutions while scaling to larger problem instances than existing methods. We demonstrate the effectiveness of our approach by comparing it with several baseline algorithms on a city road network and analyzing the quality of the solutions obtained. Our work contributes to the field of robot planning by addressing the critical issue of incorporating human assistance and environmental restrictions, which has significant implications for real-world applications.

翻译：本文针对人机协作团队中机器人的最优规划问题提出了一种解决方案，其中人类监督员间歇性地为机器人提供协助以加速任务完成。具体而言，我们研究了在机器人等待协助的时间受到环境约束的条件下，如何计算两个位形之间的最短路径这一挑战性问题。为解决该问题，我们提出了一种创新方法，通过引入预算和关键出发时间的概念，在获得最优解的同时，能够处理比现有方法规模更大的问题实例。通过在城区道路网络上与多个基线算法进行对比，并分析所获解的质量，验证了本方法的有效性。我们的工作通过整合人类协助与环境限制这一关键难题，为机器人规划领域做出了贡献，这对实际应用具有重要的现实意义。