Multi-Robot Navigation Among Movable Obstacles: Implicit Coordination to Deal with Conflicts and Deadlocks

How to coordinate multiple robots moving in modifiable cluttered environments? In this paper, we introduce the multi-robot version of the NAMO problem (Navigation Among Movable Obstacles). In MR-NAMO, robots must not only plan for the possibility of displacing obstacles as needed to facilitate their navigation, but also solve conflicts that may arise when trying to simultaneously access a location or obstacle. After identifying all different types of conflicts, we define and compare variants of an implicit coordination strategy allowing the use of existing NAMO algorithms [1] in a Multi-Robot context. We also show how our previously introduced social occupation cost model [2] can improve the efficiency of multirobot plans with better obstacle placement choices, and how it can be applied in a novel way to find relevant robot placement choices to solve deadlock situations.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802092
Citations
3
Primary Topic
Optimization and Search Problems
Type
article
Field-Weighted Citation Impact
1.05
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article

Multi-Robot Navigation Among Movable Obstacles: Implicit Coordination to Deal with Conflicts and Deadlocks

David J. Brown, Jacques Saraydaryan, Benoit Renault, Olivier Simonin
3 citations
Optimization and Search Problems
1.05
article

Multi-Robot Navigation Among Movable Obstacles: Implicit Coordination to Deal with Conflicts and Deadlocks

David J. Brown, Jacques Saraydaryan, Benoit Renault, Olivier Simonin
article en
3 citations

Abstract

How to coordinate multiple robots moving in modifiable cluttered environments? In this paper, we introduce the multi-robot version of the NAMO problem (Navigation Among Movable Obstacles). In MR-NAMO, robots must not only plan for the possibility of displacing obstacles as needed to facilitate their navigation, but also solve conflicts that may arise when trying to simultaneously access a location or obstacle. After identifying all different types of conflicts, we define and compare variants of an implicit coordination strategy allowing the use of existing NAMO algorithms [1] in a Multi-Robot context. We also show how our previously introduced social occupation cost model [2] can improve the efficiency of multirobot plans with better obstacle placement choices, and how it can be applied in a novel way to find relevant robot placement choices to solve deadlock situations.

Institut national de recherche en sciences et technologies du numérique (FR), Citigroup (US), Institut National des Sciences Appliquées de Lyon (FR), École d'Ingénieurs en Chimie et Sciences du Numérique (FR)
Climate action
Openalex Percentile: Top 21%
Optimization and Search Problems
1.05
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Multi-Robot Navigation Among Movable Obstacles: Implicit Coordination to Deal with Conflicts and Deadlocks — David J. Brown, Jacques Saraydaryan, et al. · (2024) | TGRS Research Map | TGRS