# Distributed Simultaneous Action and Target Assignment for Multi-Robot Multi-Target Tracking

## TL;DR

This paper presents a distributed algorithm for multi-robot multi-target tracking that efficiently assigns robots to targets despite sensing and communication limitations, with proven theoretical bounds and effective simulation results.

## Contribution

It introduces a novel distributed local algorithm based on max-min linear programs for multi-robot multi-target assignment with theoretical performance guarantees.

## Key findings

- The algorithm provides bounds on running time and approximation ratio.
- Simulation results demonstrate the effectiveness of the local algorithm.
- The approach addresses sensing and communication constraints in multi-robot systems.

## Abstract

We study a multi-robot assignment problem for multi-target tracking. The proposed problem can be viewed as the mixed packing and covering problem. To deal with a limitation on both sensing and communication ranges, a distributed approach is taken into consideration. A local algorithm gives theoretical bounds on both the running time and approximation ratio to an optimal solution. We employ a local algorithm of max-min linear programs to solve the proposed task. Simulation result shows that a local algorithm is an effective solution to the multi-robot task allocation.