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Computer Science > Robotics

arXiv:2108.00745 (cs)
[Submitted on 2 Aug 2021 (v1), last revised 4 Mar 2022 (this version, v3)]

Title:Multi-objective Conflict-based Search Using Safe-interval Path Planning

Authors:Zhongqiang Ren, Sivakumar Rathinam, Maxim Likhachev, Howie Choset
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Abstract:This paper addresses a generalization of the well known multi-agent path finding (MAPF) problem that optimizes multiple conflicting objectives simultaneously such as travel time and path risk. This generalization, referred to as multi-objective MAPF (MOMAPF), arises in several applications ranging from hazardous material transportation to construction site planning. In this paper, we present a new multi-objective conflict-based search (MO-CBS) approach that relies on a novel multi-objective safe interval path planning (MO-SIPP) algorithm for its low-level search. We first develop the MO-SIPP algorithm, show its properties and then embed it in MO-CBS. We present extensive numerical results to show that (1) there is an order of magnitude improvement in the average low level search time, and (2) a significant improvement in the success rates of finding the Pareto-optimal front can be obtained using the proposed approach in comparison with the previous MO-CBS.
Comments: 8 pages
Subjects: Robotics (cs.RO); Artificial Intelligence (cs.AI)
Cite as: arXiv:2108.00745 [cs.RO]
  (or arXiv:2108.00745v3 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2108.00745

Submission history

From: Zhongqiang Ren [view email]
[v1] Mon, 2 Aug 2021 09:42:08 UTC (3,346 KB)
[v2] Wed, 8 Sep 2021 21:58:12 UTC (3,411 KB)
[v3] Fri, 4 Mar 2022 19:19:24 UTC (2,228 KB)
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