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Main Authors: Li, Kang, Li, Ming, Ji, Wenkang, Sun, Zhiyong, Zhao, Shiyu
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2507.10249
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author Li, Kang
Li, Ming
Ji, Wenkang
Sun, Zhiyong
Zhao, Shiyu
author_facet Li, Kang
Li, Ming
Ji, Wenkang
Sun, Zhiyong
Zhao, Shiyu
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2507_10249
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Multi-Robot Cooperative Herding through Backstepping Control Barrier Functions
Li, Kang
Li, Ming
Ji, Wenkang
Sun, Zhiyong
Zhao, Shiyu
Multiagent Systems
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.
title Multi-Robot Cooperative Herding through Backstepping Control Barrier Functions
topic Multiagent Systems
url https://arxiv.org/abs/2507.10249