A Novel Cooperative Path Planning for Multi-robot Persistent Coverage with Obstacles and Coverage Period Constraints.

Guibin Sun,Rui Zhou,Bin Di,Zhuoning Dong,Yingxun Wang

doi:10.3390/s19091994

Guibin Sun, Rui Zhou + Show 3 more

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https://doi.org/10.3390/s19091994

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Abstract

In this paper, a multi-robot persistent coverage of the region of interest is considered, where persistent coverage and cooperative coverage are addressed simultaneously. Previous works have mainly concentrated on the paths that allow for repeated coverage, but ignored the coverage period requirements of each sub-region. In contrast, this paper presents a combinatorial approach for path planning, which aims to cover mission domains with different task periods while guaranteeing both obstacle avoidance and minimizing the number of robots used. The algorithm first deploys the sensors in the region to satisfy coverage requirements with minimum cost. Then it solves the travelling salesman problem to obtain the frame of the closed path. Finally, the approach partitions the closed path into the fewest segments under the coverage period constraints, and it generates the closed route for each robot on the basis of portioned segments of the closed path. Therefore, each robot can circumnavigate one closed route to cover the different task areas completely and persistently. The numerical simulations show that the proposed approach is feasible to implement the cooperative coverage in consideration of obstacles and coverage period constraints, and the number of robots used is also minimized.

Highlights

Research interest for the coverage and coordination of multi-agent has shown an increase in the field of artificial intelligence (AI) and control [1,2,3,4,5,6]
This paper presents a new combinatorial approach for cooperative multi-robot path planning, which focuses on the persistent coverage problem with obstacles and different coverage period constraints using the minimum number of robots
In viewInof theoffacts thatthat previous works regarding coverage period constraints in view the facts previous worksneglected neglected regarding thethe coverage period constraints in differentdifferent sub-regions and the number of robots used for persistent coverage task, this paper proposes sub-regions and the number of robots used for persistent coverage task, this paper proposes the combined above combined method cooperativemulti-robot multi-robot persistent coverage

Summary

Introduction

Research interest for the coverage and coordination of multi-agent has shown an increase in the field of artificial intelligence (AI) and control [1,2,3,4,5,6]. Coverage control using multiple robots with limited sensing capabilities has received significant attention recently due to its versatility in many applications, such as mapping, patrolling, surveillance, and complete coverage [3,4,5,6,7,8,9,10,11]. It is more difficult to achieve persistent coverage for a group of multiple robots considering obstacle avoidance and coverage period, because mission domains may have differently shaped obstacles, as well as more complicated constraints. The literature [13] develops two efficient coverage strategies for multiple robots based on boustrophedon cellular decomposition to achieve complete coverage of a known environment. Votion and Cao first develop three improved A-star algorithms to obtain the optimal path, and they present a new spatially diverse path planning algorithm based on the A-star variants to Sensors 2019, 19, 1994; doi:10.3390/s19091994 www.mdpi.com/journal/sensors

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