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 variati...

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Bibliographic Details
Published in:Autonomous robots 2022-03, Vol.46 (3), p.469-481
Main Authors: Auletta, Fabrizia, Fiore, Davide, Richardson, Michael J., di Bernardo, Mario
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computer Imaging
Control
Engineering
Farmers
Mechatronics
Pattern Recognition and Graphics
Robotics
Robotics and Automation
Robots
Simulation
Vision
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Summary: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.
ISSN:0929-5593
1573-7527
DOI:10.1007/s10514-021-10033-6