Multi-Robot Persistent Monitoring: Minimizing Latency and Number of Robots with Recharging Constraints
Not on the map. Why?
Abstract (arXiv)
In this paper we study multi-robot path planning for persistent monitoring tasks. We consider the case where robots have a limited battery capacity with a discharge time D. We represent the areas to be monitored as the vertices of a weighted graph. For each vertex, there is a constraint on the maximum allowable time between robot visits, called the latency. The objective is to find the minimum number of robots that can satisfy these latency constraints while also ensuring that the robots periodically charge at a recharging depot. The decision version of this problem is known to be PSPACE-complete. We present a O(fraclog Dlog log Dlog ρ) approximation algorithm for the problem where ρ is the ratio of the maximum and the minimum latency constraints. We also present an orienteering based heuristic to solve the problem and show empirically that it typically provides higher quality solutions than the approximation algorithm. We extend our results to provide an algorithm for the problem of minimizing the maximum weighted latency given a fixed number of robots. We evaluate our algorithms on large problem instances in a patrolling scenario and in a wildfire monitoring application. We also compare the algorithms with an existing solver on benchmark instances.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Mar 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2026: 2.
2 papers.
- 2026Priority-Aware Multi-Robot Coverage Path Planningcited by 2
- 2026Learning to Solve Compositional Geometry Routing Problemscited by 0
- 2026Learning to Solve Compositional Geometry Routing Problems18 May 2026
- 2026Priority-Aware Multi-Robot Coverage Path Planning2 Jan 2026