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Found 4 papers, 3 papers with code
Multi-Robot Connected Fermat Spiral Coverage
We introduce the Multi-Robot Connected Fermat Spiral (MCFS), a novel algorithmic framework for Multi-Robot Coverage Path Planning (MCPP) that adapts Connected Fermat Spiral (CFS) from the computer graphics community to multi-robot coordination for the first time.
Large-Scale Multi-Robot Coverage Path Planning via Local Search
Existing graph-based MCPP algorithms first compute a tree cover on $G$ -- a forest of multiple trees that cover all vertices -- and then employ the Spanning Tree Coverage (STC) paradigm to generate coverage paths on the decomposed graph $D$ of the terrain graph $G$ by circumnavigating the edges of the computed trees, aiming to optimize the makespan (i. e., the maximum coverage path cost among all robots).
Mixed Integer Programming for Time-Optimal Multi-Robot Coverage Path Planning with Efficient Heuristics
We investigate time-optimal Multi-Robot Coverage Path Planning (MCPP) for both unweighted and weighted terrains, which aims to minimize the coverage time, defined as the maximum travel time of all robots.
Learning to Coordinate for a Worker-Station Multi-robot System in Planar Coverage Tasks
In this paper, we focus on the multi-robot coverage path planning (mCPP) problem in large-scale planar areas with random dynamic interferers in the environment, where the robots have limited resources.
