A Distributed Outmost Push Approach for Multirobot Herding

This article presents a distributed control strategy for herding groups of evaders toward a predefined goal region using a team of robotic herders. In herding problems, evaders tend to move away from each other to increase their coverage regions. This makes it challenging to develop control solution...

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Published in:	IEEE transactions on robotics Vol. 40; pp. 1706 - 1723
Main Authors:	Zhang, Shuai, Lei, Xiaokang, Duan, Mengyuan, Peng, Xingguang, Pan, Jia
Format:	Journal Article
Language:	English
Published:	New York IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Autonomous robots Decision analysis distributed robot systems Farmers Multi-robot systems Multiple robots multirobot systems Robot sensing systems robotic herding Robotics Swarm robotics
ISSN:	1552-3098, 1941-0468
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Abstract	This article presents a distributed control strategy for herding groups of evaders toward a predefined goal region using a team of robotic herders. In herding problems, evaders tend to move away from each other to increase their coverage regions. This makes it challenging to develop control solutions since the wandering evaders need to be collected while driving the herd. To address this, we propose the distributed outmost push strategy, where each robotic herder pushes the evader that is farthest from the goal region. The intuition behind this strategy is that robotic herders should focus on evaders that are further from the goal region as they are more likely to be missed during the herding process. The outmost evaders are selected from the local field of view, and the robotic herders make decisions in a decentralized manner. We also analyze the convergence of the designed dynamics and the minimum sensing range required for herders. The proposal's effectiveness and generality are validated through numerical simulations and real robotic experiments.
AbstractList	This article presents a distributed control strategy for herding groups of evaders toward a predefined goal region using a team of robotic herders. In herding problems, evaders tend to move away from each other to increase their coverage regions. This makes it challenging to develop control solutions since the wandering evaders need to be collected while driving the herd. To address this, we propose the distributed outmost push strategy, where each robotic herder pushes the evader that is farthest from the goal region. The intuition behind this strategy is that robotic herders should focus on evaders that are further from the goal region as they are more likely to be missed during the herding process. The outmost evaders are selected from the local field of view, and the robotic herders make decisions in a decentralized manner. We also analyze the convergence of the designed dynamics and the minimum sensing range required for herders. The proposal's effectiveness and generality are validated through numerical simulations and real robotic experiments.
Author	Zhang, Shuai Peng, Xingguang Lei, Xiaokang Duan, Mengyuan Pan, Jia
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Snippet	This article presents a distributed control strategy for herding groups of evaders toward a predefined goal region using a team of robotic herders. In herding...
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SubjectTerms	Autonomous robots Decision analysis distributed robot systems Farmers Multi-robot systems Multiple robots multirobot systems Robot sensing systems robotic herding Robotics Swarm robotics
Title	A Distributed Outmost Push Approach for Multirobot Herding
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