A General Framework for Dynamic MAPF using Multi-Shot ASP and Tunnels

2025-07-28

AI Summary

This paper addresses the Dynamic Multi-Agent Path Finding (D-MAPF) problem—generating collision-free, real-time paths for agents operating in environments with dynamically appearing, disappearing, or moving obstacles (e.g., human-robot collaborative warehouses). We propose a general formalization of D-MAPF and a unified solving framework. A key innovation is the “tunnel” constraint mechanism, which balances computational efficiency and robustness by bridging global replanning and local repair. Our approach employs multi-round incremental solving based on Answer Set Programming (ASP), integrating declarative modeling with environment-aware reasoning. Experimental results demonstrate that the method significantly improves the trade-off between response latency and path quality, achieving high success rates under dynamic environmental changes while maintaining low computational overhead.

Technology Category

• Multiagent Systems: Multiagent Planning
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Intelligent Robots: Motion and Path Planning

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Agentic search
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

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.

Problem

• Dynamic MAPF problem with changing agents and obstacles
• General framework for solving D-MAPF variations
• ASP-based method with tunnels for agent movement

Innovation

• Multi-shot ASP for dynamic MAPF solving
• Tunnels concept for agent movement specification
• General framework adaptable to D-MAPF variations