Multi-Agent Path Finding (MAPF) is a long-standing problem in Robotics and Artificial Intelligence in which one needs to find a set of collision-free paths for a group of mobile agents (robots) operating in the shared workspace. Due to its importance, the problem is well-studied and multiple optimal and approximate algorithms are known. However, many of them abstract away from the kinematic constraints and assume that the agents can accelerate/decelerate instantaneously. This complicates the application of the algorithms on the real robots. In this paper, we present a method that mitigates this issue to a certain extent. The suggested solver is essentially, a prioritized planner based on the well-known Safe Interval Path Planning (SIPP) algorithm. Within SIPP we explicitly reason about the speed and the acceleration thus the constructed plans directly take kinematic constraints of agents into account. We suggest a range of heuristic functions for that setting and conduct a thorough empirical evaluation of the suggested algorithm.
翻译:多代理路径发现(MAPF)是机器人和人工智能(MAPF)中长期存在的一个问题,在机器人和人工智能中,需要为在共享工作空间运行的一组移动剂(机器人)找到一套无碰撞路径。由于这一问题的重要性,这个问题是经过充分研究的,而且已知了多种最佳和近似算法。然而,其中许多是抽象的,脱离了运动限制,假设代理人可以即时加速/减速。这使算法在真实机器人中的应用复杂化。在本文中,我们提出了一个在某种程度上减轻这一问题的方法。建议的解答器基本上是一个基于众所周知的安全间路径规划(SIPPP)算法的优先规划器。在SIPP中,我们明确解释了所构建的计划的速度和加速程度,从而直接考虑到代理人的动态限制。我们建议了用于设置和对所建议的算法进行彻底经验评估的一系列超自然功能。