提出动态路径规划新框架，支持实时调整与高效避障。
A General Framework for Dynamic MAPF using Multi-Shot ASP and Tunnels
- 采用多轮求解与隧道机制，灵活应对环境变化。
- 实验显示计算效率高，路径质量优于传统方法。
- 适合仓库、人机协同等动态场景下的多智能体调度。
MAPF 问题旨在为多个智能体在给定时间内规划路径，避免彼此或障碍物碰撞。针对实际应用中计划执行与监控的需求，本文研究动态 MAPF（D-MAPF）问题，允许智能体进出环境或障碍物移动/移除等变化。考虑仓库中存在人类的现实场景，本文提出：1）一个通用的 D-MAPF 定义（适用于多种变体）；2）一个新框架，支持多轮求解并兼容不同求解方法；3）一种基于 ASP 的新方法，结合重规划与修复的优点，并引入“隧道”概念以指定智能体可移动区域。通过实验评估，从计算性能和解的质量角度验证了该方法的优势与局限。
原文摘要 · Abstract (English)
MAPF problem aims to find plans for multiple agents in an environment within a given time, such that the agents do not collide with each other or obstacles. Motivated by the execution and monitoring of these plans, we study Dynamic MAPF (D-MAPF) problem, which allows changes such as agents entering/leaving the environment or obstacles being removed/moved. Considering the requirements of real-world applications in warehouses with the presence of humans, we introduce 1) a general definition for D-MAPF (applicable to variations of D-MAPF), 2) a new framework to solve D-MAPF (utilizing multi-shot computation, and allowing different methods to solve D-MAPF), and 3) a new ASP-based method to solve D-MAPF (combining advantages of replanning and repairing methods, with a novel concept of tunnels to specify where agents can move). We have illustrated the strengths and weaknesses of this method by experimental evaluations, from the perspectives of computational performance and quality of solutions.
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