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Distributed swarm control for multi-robot systems inspired by shepherding behaviors

Science China(Technological Sciences) 2024年第7期67卷 2191-2202页

作者： SUN GuiBin GU HaiBo LÜJinHu School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100094China

swarming behaviors play an eminent role in both biological and engineering research, and show great potential applications in many emerging fields. Traditional swarming models still lack integrity, uniformity, and stability in swarm forming processes,resulting in fragmentation and void phenomena. Inspired by the shepherding behaviors observed in nature, we propose an integrated negotiation-control scheme for distributed swarm control of massive robots. The core idea of this scheme is that the robots at the boundary of the group herd the internal robots to form an equilibrium swarm. For this purpose, we introduce a concept of virtual group center towards which boundary robots herd internal robots. Then, a distributed negotiation mechanism is designed to allow each robot to negotiate the virtual group center only through local interactions with its neighbors. After that, we propose a shepherding-inspired swarm control law to drive a group of robots to form an integrated, uniform, and stable configuration from any initial states. Both numerical and flight simulations are presented to verify the effectiveness of our proposed swarm control scheme.

关键词： swarm control multi-robot system negotiation-control scheme shepherding behavior

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Reinforcement Learning Methods in Robotic Fish: Survey

Reinforcement Learning Methods in Robotic Fish: Survey

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第43届中国控制会议

作者： Penghang Shuai Haipeng Li Yongkang Luo Liangwei Deng The Laboratory of Cognition and Decision Intelligence for Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences

Reinforcement learning control has gained increasing attention in the field of biomimetic robotic fish, due to its advantage of universal applicability without prior knowledge of dynamic modeling. In this paper, we review the research work on the application of reinforcement learning in the field of robotic fish. We present and discuss the general model of applying reinforcement learning approaches to robotic fish control, such as the design of environment, state, reward and the selection of reinforcement learning algorithm. Furthermore, we propose to divide the typical tasks of reinforcement learning applied in robotic fish into single control and swarm control, and review the recent advancements separately.

关键词： Reinforcement Learning control Robotic Fish Single control swarm control

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