# Multi-Robot Routing for Persistent Monitoring with Latency Constraints

## TL;DR

This paper addresses multi-robot persistent monitoring with latency constraints, proposing approximation and heuristic algorithms, and demonstrating their effectiveness through simulations and benchmarks.

## Contribution

It introduces a $O(\log
ho)$ approximation algorithm and a heuristic for multi-robot routing under latency constraints, with empirical evaluation.

## Key findings

- Heuristic often outperforms the approximation algorithm in simulations.
- Algorithms effectively handle large problem instances.
- Comparison with existing solvers shows competitive performance.

## Abstract

In this paper we study a multi-robot path planning problem for persistent monitoring of an environment. We represent the areas to be monitored as the vertices of a weighted graph. For each vertex, there is a constraint on the maximum time spent by the robots between visits to that vertex, called the latency, and the objective is to find the minimum number of robots that can satisfy these latency constraints. The decision version of this problem is known to be PSPACE-complete. We present a $O(\log \rho)$ approximation algorithm for the problem where $\rho$ is the ratio of the maximum and the minimum latency constraints. We also present an orienteering based heuristic to solve the problem and show through simulations that in most of the cases the heuristic algorithm gives better solutions than the approximation algorithm. We evaluate our algorithms on large problem instances in a patrolling scenario and in a persistent scene reconstruction application. We also compare the algorithms with an existing solver on benchmark instances.