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Mario Di Bernardo

1 accepted papers

2026

Multi-Robot Obstacle-Aware Shepherding of Non-Cohesive Target Agents

ICRA 2026poster

This paper presents a novel control strategy for multi-agent shepherding of non-cohesive targets in obstacle-rich environments. Unlike previous approaches that assume cohesive flocking behavior, our method handles targets that interact only with nearby herders through repulsive forces and exhibit no…