Multi-Robot Cooperative Herding through Backstepping Control Barrier Functions

TL;DR

This paper introduces a novel multi-robot herding strategy using backstepping control barrier functions to coordinate herders in safely guiding evaders to a goal, ensuring safety and effectiveness.

Contribution

It develops a hierarchical backstepping CBF-based control method for underactuated multi-robot herding, with centralized and decentralized implementations, validated through simulations and experiments.

Findings

Effective herding of multiple evaders demonstrated

Safety guarantees maintained during herding process

Both simulation and real-world experiments confirm strategy efficacy

Abstract

We propose a novel cooperative herding strategy through backstepping control barrier functions (CBFs), which coordinates multiple herders to herd a group of evaders safely towards a designated goal region. For the herding system with heterogeneous groups involving herders and evaders, the behavior of the evaders can only be influenced indirectly by the herders' motion, especially when the evaders follow an inverse dynamics model and respond solely to repulsive interactions from the herders. This indirect interaction mechanism inherently renders the overall system underactuated. To address this issue, we first construct separate CBFs for the dual objectives of goal reaching and collision avoidance, which ensure both herding completion and safety guarantees. Then, we reformulate the underactuated herding dynamics into a control-affine structure and employ a backstepping approach to recursively design control inputs for the hierarchical barrier functions, avoiding taking derivatives of the higher-order system. Finally, we present a cooperative herding strategy based on backstepping CBFs that allow herders to safely herd multiple evaders into the goal region. In addition, centralized and decentralized implementations of the proposed algorithm are developed, further enhancing its flexibility and applicability. Extensive simulations and real-world experiments validate the effectiveness and safety of the proposed strategy in multi-robot herding.