TY - GEN

T1 - Multi-train path finding

AU - Atzmon, Dor

AU - Diei, Amit

AU - Rave, Daniel

N1 - Publisher Copyright:
Copyright © 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Multi-agent path finding (MAPF) is the problem of moving a set of agents from their individual start locations to their individual goal locations, without collisions. This problem has practical applications in video games, traffic control, robotics, and more. In MAPF we assume that agents occupy one location each time step. However, in real life some agents have different size or shape. Hence, a standard MAPF solution may be not suited in practice for some applications. In this paper, we describe a novel algorithm, based on the CBS algorithm, that finds a plan for moving a set of train-agents, i.e., agents that occupy a sequence of two or more locations, such as trains, buses, planes, or even snakes. We prove that our solution is optimal and show experimentally that indeed such a solution can be found. Finally, we explain how our solution can also apply to agents with any geometric shape.

AB - Multi-agent path finding (MAPF) is the problem of moving a set of agents from their individual start locations to their individual goal locations, without collisions. This problem has practical applications in video games, traffic control, robotics, and more. In MAPF we assume that agents occupy one location each time step. However, in real life some agents have different size or shape. Hence, a standard MAPF solution may be not suited in practice for some applications. In this paper, we describe a novel algorithm, based on the CBS algorithm, that finds a plan for moving a set of train-agents, i.e., agents that occupy a sequence of two or more locations, such as trains, buses, planes, or even snakes. We prove that our solution is optimal and show experimentally that indeed such a solution can be found. Finally, we explain how our solution can also apply to agents with any geometric shape.

UR - http://www.scopus.com/inward/record.url?scp=85076096297&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85076096297

T3 - Proceedings of the 12th International Symposium on Combinatorial Search, SoCS 2019

SP - 125

EP - 129

BT - Proceedings of the 12th International Symposium on Combinatorial Search, SoCS 2019

A2 - Surynek, Pavel

A2 - Yeoh, William

PB - AAAI press

T2 - 12th International Symposium on Combinatorial Search, SoCS 2019

Y2 - 16 July 2019 through 17 July 2019

ER -