Multi-Robot Target Tracking with Sensing and Communication Danger Zones

TL;DR

This paper develops a risk-aware multi-robot tracking framework that considers environmental hazards, enabling robots to adaptively avoid danger zones in uncertain and adversarial environments, validated through simulations and real-world drone experiments.

Contribution

It introduces a novel risk-aware multi-robot tracking approach that models environmental hazards and optimizes robot behavior under uncertainty, addressing limitations of traditional methods.

Findings

Robots effectively avoid danger zones in simulations.

The framework maintains tracking accuracy under environmental uncertainty.

Real-world drone experiments confirm practical effectiveness.

Abstract

Multi-robot target tracking finds extensive applications in different scenarios, such as environmental surveillance and wildfire management, which require the robustness of the practical deployment of multi-robot systems in uncertain and dangerous environments. Traditional approaches often focus on the performance of tracking accuracy with no modeling and assumption of the environments, neglecting potential environmental hazards which result in system failures in real-world deployments. To address this challenge, we investigate multi-robot target tracking in the adversarial environment considering sensing and communication attacks with uncertainty. We design specific strategies to avoid different danger zones and proposed a multi-agent tracking framework under the perilous environment. We approximate the probabilistic constraints and formulate practical optimization strategies to address computational challenges efficiently. We evaluate the performance of our proposed methods in simulations to demonstrate the ability of robots to adjust their risk-aware behaviors under different levels of environmental uncertainty and risk confidence. The proposed method is further validated via real-world robot experiments where a team of drones successfully track dynamic ground robots while being risk-aware of the sensing and/or communication danger zones.