TY - JOUR

T1 - Coordination of Multiple Robots along Given Paths with Bounded Junction Complexity

AU - Abrahamsen, Mikkel

AU - Geft, Tzvika

AU - Halperin, Dan

AU - Ugav, Barak

N1 - Publisher Copyright:
© 2023 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

PY - 2023

Y1 - 2023

N2 - We study a fundamental NP-hard motion coordination problem for multi-robot/multi-agent systems: We are given a graph G and set of agents, where each agent has a given directed path in G. Each agent is initially located on the first vertex of its path. At each time step an agent can move to the next vertex on its path, provided that the vertex is not occupied by another agent. The goal is to find a sequence of such moves along the given paths so that each agent reaches its target or to report that no such sequence exists. The problem models guidepath-based transport systems, which is a pertinent abstraction for traffic in a variety of contemporary applications, ranging from train networks or Automated Guided Vehicles (AGVs) in factories, through computer game animations, to qubit transport in quantum computing. It also arises as a sub-problem in the more general multi-robot motion-planning problem. We provide a fine-grained tractability analysis of the problem by considering new assumptions and identifying minimal values of key parameters for which the problem remains NP-hard. Our analysis identifies a critical parameter called vertex multiplicity (VM), defined as the maximum number of paths passing through the same vertex. We show that a prevalent variant of the problem, which is equivalent to Sequential Resource Allocation (concerning deadlock prevention for concurrent processes), is NP-hard even when VM is 3. On the positive side, for VM ≤ 2 we give an efficient algorithm that iteratively resolves cycles of blocking relations among agents. We also present a variant that is NP-hard when the VM is 2 even when G is a 2D grid and each path lies in a single grid row or column. By studying highly distilled yet NP-hard variants, we deepen the understanding of what makes the problem intractable and thereby guide the search for efficient solutions.

AB - We study a fundamental NP-hard motion coordination problem for multi-robot/multi-agent systems: We are given a graph G and set of agents, where each agent has a given directed path in G. Each agent is initially located on the first vertex of its path. At each time step an agent can move to the next vertex on its path, provided that the vertex is not occupied by another agent. The goal is to find a sequence of such moves along the given paths so that each agent reaches its target or to report that no such sequence exists. The problem models guidepath-based transport systems, which is a pertinent abstraction for traffic in a variety of contemporary applications, ranging from train networks or Automated Guided Vehicles (AGVs) in factories, through computer game animations, to qubit transport in quantum computing. It also arises as a sub-problem in the more general multi-robot motion-planning problem. We provide a fine-grained tractability analysis of the problem by considering new assumptions and identifying minimal values of key parameters for which the problem remains NP-hard. Our analysis identifies a critical parameter called vertex multiplicity (VM), defined as the maximum number of paths passing through the same vertex. We show that a prevalent variant of the problem, which is equivalent to Sequential Resource Allocation (concerning deadlock prevention for concurrent processes), is NP-hard even when VM is 3. On the positive side, for VM ≤ 2 we give an efficient algorithm that iteratively resolves cycles of blocking relations among agents. We also present a variant that is NP-hard when the VM is 2 even when G is a 2D grid and each path lies in a single grid row or column. By studying highly distilled yet NP-hard variants, we deepen the understanding of what makes the problem intractable and thereby guide the search for efficient solutions.

KW - complexity

KW - multi-agent path finding

KW - multi-robot motion planning

KW - predefined paths

KW - scheduling

KW - sequential resource allocation

UR - http://www.scopus.com/inward/record.url?scp=85162692067&partnerID=8YFLogxK

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AN - SCOPUS:85162692067

SN - 1548-8403

VL - 2023-May

SP - 932

EP - 940

JO - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS

JF - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS

T2 - 22nd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023

Y2 - 29 May 2023 through 2 June 2023

ER -