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Motion Coordination of Multi-Agent Networks for Multiple Target Tracking with Guaranteed Collision Avoidance

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Abstract

We address a decentralized control problem for a multi-agent network whose goal is to track a moving multi-target system over a cluttered environment. Our problem is comprised of two interconnected problems. In the first problem, we aim to find a reference density path for the multi-target system that the multi-agent network must track as a whole. In our proposed solution approach, the probability density of the multi-target system is represented as a Gaussian mixture density which is estimated by an adaptive Gaussian sum filter. The second problem seeks for the individual inputs that will make the agents follow the moving targets while avoiding collisions. To address the latter problem, we propose a control algorithm which is based on a variation of Lloyd’s algorithm that utilizes the Gaussian mixture density computed as part of the solution to the first problem and a modified Voronoi tessellation which is composed of the so-called Obstacle-Aware Voronoi Cells. Because the two sub-problems are interconnected, an iterative approach is proposed which combines their solutions to solve the multi-target tracking problem in a comprehensive and safe way. Finally, we provide simulation results to showcase the effectiveness of our proposed approach.

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  1. Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Street, Austin, 78712-1221, Texas, USA

    Alaa Z. Abdulghafoor & Efstathios Bakolas

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  1. Alaa Z. Abdulghafoor
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All authors contributed to the study conception and design. Alaa Z. Abdulghafoor contributed to the following tasks: conceptualization, methodology, software, writing-original draft preparation, validation, visualization, investigation, and formal analysis. Efstathios Bakolas contributed to the following tasks: supervision, methodology, writing-reviewing and editing, and formal analysis. All authors read and approved the final manuscript.

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Abdulghafoor, A.Z., Bakolas, E. Motion Coordination of Multi-Agent Networks for Multiple Target Tracking with Guaranteed Collision Avoidance. J Intell Robot Syst 107, 5 (2023). https://doi.org/10.1007/s10846-022-01786-y

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