Complete Decentralized Method for On-Line Multi-Robot Trajectory Planning in Well-formed Infrastructures

Ćáp, Michal; Vokřínek, Jiří; Kleiner, Alexander

doi:10.1609/icaps.v25i1.13696

Cited by 31 publications

(17 citation statements)

References 15 publications

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“…Sketch of Proof. It has been shown before that prioritized planner relying on the complete individual pathfinding algorithm that takes into account previously found trajectories as fixed obstacles in space-time, is complete in WFI Čáp, Vokřínek, and Kleiner 2015). Thus, as AA-SIPP is complete, AA-SIPP(m) is also complete.…”

Section: Aa-sipp and Aa-sipp(m) Propertiesmentioning

confidence: 99%

Any-Angle Pathfinding for Multiple Agents Based on SIPP Algorithm

Yakovlev

Andreychuk

2017

ICAPS

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The problem of finding conflict-free trajectories for multiple agents of identical circular shape, operating in shared 2D workspace, is addressed in the paper and decoupled, e.g., prioritized, approach is used to solve this problem. Agents' workspace is tessellated into the square grid on which any-angle moves are allowed, e.g. each agent can move into an arbitrary direction as long as this move follows the straight line segment whose endpoints are tied to the distinct grid elements. A novel any-angle planner based on Safe Interval Path Planning (SIPP) algorithm is proposed to find trajectories for an agent moving amidst dynamic obstacles (other agents) on a grid. This algorithm is then used as part of a prioritized multi-agent planner AA-SIPP(m). On the theoretical side, we show that AA-SIPP(m) is complete under well-defined conditions. On the experimental side, in simulation tests with up to 250 agents involved, we show that our planner finds much better solutions in terms of cost (up to 20%) compared to the planners relying on cardinal moves only.

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Section: Aa-sipp and Aa-sipp(m) Propertiesmentioning

confidence: 99%

Any-Angle Pathfinding for Multiple Agents Based on SIPP Algorithm

Yakovlev

Andreychuk

2017

ICAPS

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“…These methods [3], [4], [5] generally provide low-quality solutions because they plan subpaths for several updated agents, rather than all paths. Furthermore, they are applicable only to well-formed maps [26], where each agent may rest at an isolated goal or parking location that is not blocked from other agents. Li et al [6] proposed the RHCR method to address these issues.…”

Section: A Lifelong Mapfmentioning

confidence: 99%

Anytime Lifelong Multi-Agent Pathfinding in Topological Maps

Song

2023

IEEE Access

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This study addresses a lifelong multi-agent path finding (lifelong MAPF) problem that continuously solves an MAPF instance online according to newly assigned goals. Specifically, we focus on lifelong MAPF in a topological map. This problem is challenging because the movement of the agent is restricted to narrow corridors in a topological map, rather than the entire map area. Bypasses may be limited or farther away in corridors, significantly complicating the computation of paths. Furthermore, low-quality solutions may cause traffic congestion or even deadlock in a corridor. Therefore, we propose a novel lifelong MAPF method that effectively resolves conflicts in corridors based on an anytime strategy. This method gradually improves the solution quality by updating sub-paths with heavy traffic congestion. Furthermore, we adopt several improvement steps to effectively resolve corridor conflicts in a conflict-based search (CBS). This method significantly reduces the search space and computation time of CBS. We conducted extensive experiments on various topological maps in warehouse and railway environments. The results show that the proposed method outperforms state-of-the-art methods in terms of throughput and success rate. In particular, the proposed method can resolve collisions with a longer time horizon than existing methods, considerably improving throughput on a topological map with long-range corridors and heavy traffic congestion.INDEX TERMS Multi-agent pathfinding, mobile robots, logistics automation, path planning, multi-robot system, topological map.

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“…Although there are several studies on planning and execution in MAPF and MAPD, most studies assumed grid-like environments, such as an automated warehouse wherein (1) there are many endpoints more than agents and (2) the agents move at a constant speed and move synchronously [13]. Moreover, these conventional methods require a well-formed infrastructure conditions (WFI conditions) [23]. For example, in the holding task endpoint (HTE) [13], any path connecting a pair of endpoints does not traverse any other endpoints.…”

Section: Introductionmentioning

confidence: 99%

Distributed Planning with Asynchronous Execution with Local Navigation for Multi-agent Pickup and Delivery Problem

Miyashita¹,

Yamauchi²,

Sugawara³

2023

Preprint

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We propose a distributed planning method with asynchronous execution for multi-agent pickup and delivery (MAPD) problems for environments with occasional delays in agents' activities and flexible endpoints. MAPD is a crucial problem framework with many applications; however, most existing studies assume ideal agent behaviors and environments, such as a fixed speed of agents, synchronized movements, and a well-designed environment with many short detours for multiple agents to perform tasks easily. However, such an environment is often infeasible; for example, the moving speed of agents may be affected by weather and floor conditions and is often prone to delays. The proposed method can relax some infeasible conditions to apply MAPD in more realistic environments by allowing fluctuated speed in agents' actions and flexible working locations (endpoints). Our experiments showed that our method enables agents to perform MAPD in such an environment efficiently, compared to the baseline methods. We also analyzed the behaviors of agents using our method and discuss the limitations.

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Complete Decentralized Method for On-Line Multi-Robot Trajectory Planning in Well-formed Infrastructures

Cited by 31 publications

References 15 publications

Any-Angle Pathfinding for Multiple Agents Based on SIPP Algorithm

Any-Angle Pathfinding for Multiple Agents Based on SIPP Algorithm

Anytime Lifelong Multi-Agent Pathfinding in Topological Maps

Distributed Planning with Asynchronous Execution with Local Navigation for Multi-agent Pickup and Delivery Problem

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