A Continuification-Based Control Solution for Large-Scale Shepherding

2024/11/07 by Di Lorenzo, Beniamino, Maffettone, Gian Carlo, di Bernardo, Mario · 2 citations
#FOS: Electrical engineering #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.2411.04791

Abstract

In this paper, we address the large-scale shepherding control problem using a continuification-based strategy. We consider a scenario in which a large group of follower agents (targets) must be confined within a designated goal region through indirect interactions with a controllable set of leader agents (herders). Our approach transforms the microscopic agent-based dynamics into a macroscopic continuum model via partial differential equations (PDEs). This formulation enables efficient, scalable control design for the herders' behavior, with guarantees of global convergence. Numerical and experimental validations in a mixed-reality swarm robotics framework demonstrate the method's effectiveness.

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• Sparse shepherding control of large-scale multi-agent systems via Reinforcement Learning
• Hierarchical Learning-Based Control for Multi-Agent Shepherding of Stochastic Autonomous Agents

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