Efficient Multi-Robot Coverage of a Known Environment

TL;DR

This paper introduces two heuristic algorithms for multi-robot area coverage in known environments, improving efficiency and workload distribution while ensuring complete coverage despite the NP-completeness of the problem.

Contribution

It presents two novel approximation heuristics for multi-robot coverage, extending single-robot algorithms and dividing areas for efficient multi-robot deployment.

Findings

Both algorithms achieve good coverage distribution among robots.

The approaches minimize individual robot workload.

Complete coverage is guaranteed with the proposed heuristics.

Abstract

This paper addresses the complete area coverage problem of a known environment by multiple-robots. Complete area coverage is the problem of moving an end-effector over all available space while avoiding existing obstacles. In such tasks, using multiple robots can increase the efficiency of the area coverage in terms of minimizing the operational time and increase the robustness in the face of robot attrition. Unfortunately, the problem of finding an optimal solution for such an area coverage problem with multiple robots is known to be NP-complete. In this paper we present two approximation heuristics for solving the multi-robot coverage problem. The first solution presented is a direct extension of an efficient single robot area coverage algorithm, based on an exact cellular decomposition. The second algorithm is a greedy approach that divides the area into equal regions and applies an efficient single-robot coverage algorithm to each region. We present experimental results for two algorithms. Results indicate that our approaches provide good coverage distribution between robots and minimize the workload per robot, meanwhile ensuring complete coverage of the area.