KMS Chongqing Institute of Green and Intelligent Technology, CAS
| Multi-robot competitive tracking based on k-WTA neural network with one single neuron | |
Peng, Bo1,2 ; Jin, Long1 ; Shang, Mingsheng1
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| 2021-10-14 | |
| 摘要 | A k-winners-take-all (k-WTA) neural network is designed and applied to a task assignment problem in a multi-robot competitive target tracking scenario in this paper. The proposed neural network features a single neuron and a non-hard-limiting activation function, which greatly simplifies the model structure and reduces the computation cost. This neural network has finite-time convergence property and can be applied to real-time situations. The stability and convergence property of the neural network is theoretically analyzed. Simulations of handling a situation that a target moves at a higher speed than tracking robots are conducted to demonstrate the effectiveness of the designed scheme. (c) 2021 Elsevier B.V. All rights reserved. |
| 关键词 | Target tracking k-winners-take-all Recurrent neural networks Finite-time convergence Global stability |
| DOI | 10.1016/j.neucom.2021.07.020 |
| 发表期刊 | NEUROCOMPUTING
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| ISSN | 0925-2312 |
| 卷号 | 460页码:1-8 |
| 通讯作者 | Jin, Long(ljin.ir@gmail.com) ; Shang, Mingsheng(msshang@cigit.ac.cn) |
| 收录类别 | SCI |
| WOS记录号 | WOS:000696919200001 |
| 语种 | 英语 |
