Herding stochastic autonomous agents via local control rules and online target selection strategies

We propose a simple yet effective set of local control rules to make a small group of herder agents collect and contain in a desired region a large ensemble of non-cooperative, non-flocking stochastic target agents in the plane. We investigate the robustness of the proposed strategies to variations of the number of target agents and the strength of the repulsive force they feel when in proximity of the herders. The effectiveness of the proposed approach is confirmed in both simulations in ROS and experiments on real robots.

Automated summary

This article proposes a simple yet effective set of local control rules for a small group of herder agents to collect and contain a large ensemble of non-cooperative, non-flocking stochastic target agents in the plane. The robustness of the proposed strategies to variations in the number of target agents and the strength of the repulsive force they experience when near the herders is investigated. The effectiveness of the proposed approach is confirmed through simulations in ROS and experiments on real robots.