Adapting to planning failures in lifelong multi-agent path finding

Jonathan Morag, Roni Stern, Ariel Felner

Research output: Contribution to journalConference articlepeer-review

Abstract

Multi-Agent Path Finding (MAPF) is the problem of finding collision-free paths for multiple agents operating in the same environment. In Lifelong MAPF (LMAPF), these agents continuously receive new destinations, and the task is to constantly update their paths while optimizing for a high throughput over time. Therefore, many MAPF sub-problems must be solved over time in order to solve a single LMAPF problem. LMAPF problems manifest in real-world applications, such as automated warehouses, where strict responsiveness requirements limit the amount of time allocated to planning. MAPF algorithms occasionally fail to produce a plan within the allotted time. We propose a system design for LMAPF that is robust to such planning failures. Then, we explore different approaches to avoid planning failures, reduce their severity, and handle them when they occur. In particular, we describe and analyze different Fail Policies that are applied when planning failures occur and ensure collisions and unnecessary degradation of throughput are avoided. To our knowledge, while such Fail Policies are used in practice in the industry, they have yet to be researched academically.

Original languageEnglish
Pages (from-to)47-55
Number of pages9
JournalThe International Symposium on Combinatorial Search
Volume16
Issue number1
DOIs
StatePublished - 2023
Externally publishedYes
Event16th International Symposium on Combinatorial Search, SoCS 2023 - Prague, Czech Republic
Duration: 14 Jul 202316 Jul 2023

Bibliographical note

Publisher Copyright:
© 2023, Association for the Advancement of Artificial Intelligence (www.aaai.org).

Fingerprint

Dive into the research topics of 'Adapting to planning failures in lifelong multi-agent path finding'. Together they form a unique fingerprint.

Cite this