首页|Automatic synthesizing multi-robot cooperation strategies based on Brain Storm Robotics
Automatic synthesizing multi-robot cooperation strategies based on Brain Storm Robotics
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NSTL
Elsevier
With the increasing task complexity and environmental uncertainty, it is hard to achieve adaptability and robustness by manual design methods for multi-robot cooperation tasks. Automatic synthesis approaches with trial and error mechanisms are getting more and more attention. By encoding the strategies to be designed as "ideas'', the newly proposed Brain Storm Robotics (BSR) framework can obtain the sufficiently good solutions for particular tasks after a series of operations on the ideas. However, the original BSR only shows designing the rule base for a fuzzy controller. This paper proposes an automatic design approach for neural network-based strategies for robotic swarms with the BSR framework to realize cooperative behaviors. Two design cases are studied: one is the direct strategy search for a swarm aggregation behavior; the other is synthesizing a backpropagation neural network-based controller for coordinated formation control, which has both evolution and learning characteristics. The results show that the proposed method can automatically find control strategies with scalability for multi-robot cooperation, which has the potential for further development. (C) 2022 Elsevier B.V. All rights reserved.
NSTL
Elsevier
