A Cooperative Multi-Agent Probabilistic Framework for Search and Track Missions

TL;DR

This paper introduces a scalable multi-agent framework for cooperative search and tracking of multiple moving targets with unknown numbers, utilizing recursive SAT-density computations for decentralized decision-making.

Contribution

It presents a novel recursive SAT-density approach and decentralized strategies for efficient multi-target search and tracking in uncertain environments.

Findings

Effective detection of unknown number of targets

Scalable decentralized search strategies

Robust performance in dynamic environments

Abstract

In this work a robust and scalable cooperative multi-agent searching and tracking framework is proposed. Specifically, we study the problem of cooperative searching and tracking of multiple moving targets by a group of autonomous mobile agents with limited sensing capabilities. We assume that the actual number of targets present is not known a priori and that target births/deaths can occur anywhere inside the surveillance region thus efficient search strategies are required to detect and track as many targets as possible. To address the aforementioned challenges we recursively compute and propagate in time the searching-and-tracking (SAT) density. Using the SAT-density, we then develop decentralized cooperative look-ahead strategies for efficient searching and tracking of an unknown number of targets inside a bounded surveillance area.