Efficient Multi-Robot Coverage of a Known Environment
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Abstract (arXiv)
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.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Aug 2018.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 3; 2025: 0; 2026: 1.
7 papers.
- 2024Large-Scale Multirobot Coverage Path Planning on Grids With Path Deconflictioncited by 5
- 2023Mixed Integer Programming for Time-Optimal Multi-Robot Coverage Path Planning with Efficient Heuristicscited by 4
- 2023Large-Scale Multi-Robot Coverage Path Planning via Local Searchcited by 3
- 2024Online Concurrent Multi-Robot Coverage Path Planningcited by 2
- 2024Multi-Robot Connected Fermat Spiral Coveragecited by 2
- 2021Dynamic Autonomous Surface Vehicle Control and Applications in Environmental Monitoringcited by 0
- 2026Coverage Path Planning: Classical Foundations, Recent Advances, and Future Directionscited by 0
- 2026Coverage Path Planning: Classical Foundations, Recent Advances, and Future Directions12 Jul 2026
- 2024Large-Scale Multirobot Coverage Path Planning on Grids With Path Deconfliction3 Nov 2024
- 2024Multi-Robot Connected Fermat Spiral Coverage20 Mar 2024
- 2024Online Concurrent Multi-Robot Coverage Path Planning15 Mar 2024
- 2023Large-Scale Multi-Robot Coverage Path Planning via Local Search17 Dec 2023
- 2023Mixed Integer Programming for Time-Optimal Multi-Robot Coverage Path Planning with Efficient Heuristics30 Jun 2023
- 2021Dynamic Autonomous Surface Vehicle Control and Applications in Environmental Monitoring29 Mar 2021