Multi-robot obstacle-aware shepherding of non-cohesive target agents

A team led by Cinzia Tomaselli at the University of Naples Federico II, in collaboration with the University of Bristol, has developed a novel control strategy for multi-robot shepherding of non-cohesive target agents in obstacle-rich environments. Unlike previous approaches that assume cohesive flocking, this method handles targets that only interact with nearby herders through repulsive forces and exhibit no inter-target coordination. Each herder employs a hybrid control policy that combines direct goal-oriented steering with obstacle-tangent maneuvering, enabling targets to circumnavigate obstacles while being guided toward a goal region. The herder dynamics integrate three key behaviors: return-to-goal motion when idle, target steering with adaptive directional control, and obstacle avoidance using both normal and tangential force components.

Numerical simulations demonstrate superior performance compared to existing shepherding methods, achieving higher target confinement rates in cluttered environments. The team validated their approach experimentally using TurtleBot4 herders and Osoyoo target robots in an indoor arena, confirming the practical effectiveness of the proposed strategy. This work, accepted at ICRA 2026, addresses a critical gap in multi-robot systems by enabling effective guidance of non-cooperative agents through complex terrains. Potential applications include environmental cleanup, wildlife management, and autonomous crowd control, where robots must guide dispersed entities without relying on internal cohesion.