GM-VPC: An Algorithm for Multi-robot Coverage of Known Spaces Using Generalized Voronoi Partition

Abstract

SUMMARYIn this paper we address the problem of coverage path planning (CPP) for multiple cooperating mobile robots. We use a ‘partition and cover’ approach using Voronoi partition to achieve natural passive cooperation between robots to avoid task duplicity. We combine two generalizations of Voronoi partition, namely geodesic-distance-based Voronoi partition and Manhattan-distance-based Voronoi partition, to address contiguity of partition in the presence of obstacles and to avoid partition-boundary-induced coverage gap. The region is divided into 2D×2D grids, where D is the size of the robot footprint. Individual robots can use any of the single-robot CPP algorithms. We show that with the proposed Geodesic-Manhattan Voronoi-partition-based coverage (GM-VPC), a complete and non-overlapping coverage can be achieved at grid level provided that the underlying single-robot CPP algorithm has similar property.We demonstrated using two representative single-robot coverage strategies, namely Boustrophedon-decomposition-based coverage and Spanning Tree coverage, first based on so-called exact cellular decomposition and second based on approximate cellular decomposition, that the proposed partitioning scheme completely eliminates coverage gaps and coverage overlaps. Simulation experiments using Matlab and V-rep robot simulator and experiments with Fire Bird V mobile robot are carried out to validate the proposed coverage strategy.

Multi-Cleaning Robots Using Cleaning Distribution Method Based on Map Decomposition in Large Environments

“…. , (17,1), (17,17) , (17,17), (13,17) , (13,5), (13,1) , and the corners of these sub-maps are shown as (1, 1), (1,17), (4, 1), . .…”

“…Therefore, R m starts exploring the traveling path at the coordinates (17, 1) and selects the edge connected with (17, 1). The edges connected to the coordinates (17, 1) are the two edges of (17, 1), (13,1) and (17,1), (17,17) . The connected corners (13,1) and (17,17) are not gray, and therefore the robot continues to search the edge.…”

“…The MRCPP methods are categorized as offline and online MRCPP methods [15], [16]. For the offline MRCPP methods [17], the environment is known in advance. Whereas, for the online MRCPP methods [18], the environment is unknown.…”

“…R m uses two convex corners of the collected corners to decompose as the decomposed edge (dotted line, −−) (1, 5), (10,5) and the decomposed edge (13,5), (13,17) . Consequently, R m collects the information for 12 edges and 10 corners as shown in Fig.…”

“…3(d). The 12 edges are at (1, 1), (1, 5) , (1,5), (1,17) , (1,17), (13,17) , (13,17), (17,17) , (17,17), (17,1) , (17, 1), (13, 1) , (13, 1), (13, 5) , (13, 5), (10, 5) , (10, 5), (10, 1) , (10, 1), (1, 1) , (1, 5), (10,5) , (13,5), (13,17) , and the 10 corners are at (1, 1), (1,5), (1,17), (13,17), (17,17), (17, 1), (13, 1), (13,5), (10,5), (10,1).…”