Noncooperative Herding With Control Barrier Functions: Theory and Experiments

TL;DR

This paper introduces a control strategy using control barrier functions for defending robots to prevent sheep-like agents from breaching protected zones, with theoretical proofs and empirical experiments demonstrating high success rates.

Contribution

It develops a reactive quadratic program-based control framework for defending robots, incorporating multiple protected zones and providing theoretical and experimental validation.

Findings

High success rates in simulations with up to ten sheep

Feasibility proven for one dog/one sheep scenario

Experimental validation on non-holonomic robots

Abstract

In this paper, we consider the problem of protecting a high-value unit from inadvertent attack by a group of agents using defending robots. Specifically, we develop a control strategy for the defending agents that we call "dog robots" to prevent a flock of "sheep agents" from breaching a protected zone. We take recourse to control barrier functions to pose this problem and exploit the interaction dynamics between the sheep and dogs to find dogs' velocities that result in the sheep getting repelled from the zone. We solve a QP reactively that incorporates the defending constraints to compute the desired velocities for all dogs. Owing to this, our proposed framework is composable \textit{i.e.} it allows for simultaneous inclusion of multiple protected zones in the constraints on dog robots' velocities. We provide a theoretical proof of feasibility of our strategy for the one dog/one sheep case. Additionally, we provide empirical results of two dogs defending the protected zone from upto ten sheep averaged over a hundred simulations and report high success rates. We also demonstrate this algorithm experimentally on non-holonomic robots. Videos of these results are available at https://tinyurl.com/4dj2kjwx.