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A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment
Li YC(李永程); Sun, Rong; Wang YC(王越超); Li HY(李洪谊); Zheng XF(郑雄飞)
作者部门机器人学研究室
发表期刊PLOS ONE
ISSN1932-6203
2016
卷号11期号:11页码:1-21
收录类别SCI
WOS记录号WOS:000386715500041
产权排序1
资助机构Research Equipment Development Program of the Chinese Academy of Sciences [YZ201545] ; National Natural Science Foundation of China [51305438] ; National High Technology Research and Development Program of China (863 Program) [2015AA020312] ; General Reserve Department of PLA [9140A26060214ZK63424]
摘要We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.
语种英语
WOS标题词Science & Technology
WOS类目Multidisciplinary Sciences
关键词[WOS]BRAIN-COMPUTER INTERFACE ; LONG-TERM POTENTIATION ; NEURONAL NETWORKS ; CORTICAL-NEURONS ; SKELETAL-MUSCLE ; STIMULATION ; DEVICES ; FABRICATION ; PLASTICITY ; ACTUATORS
WOS研究方向Science & Technology - Other Topics
引用统计
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/19479
专题机器人学研究室
通讯作者Zheng XF(郑雄飞)
作者单位1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning, P. R. China
2.University of Chinese Academy of Sciences, Beijing, P. R. China
3.Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, Anhui, P. R. China.
推荐引用方式
GB/T 7714
Li YC,Sun, Rong,Wang YC,et al. A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment[J]. PLOS ONE,2016,11(11):1-21.
APA Li YC,Sun, Rong,Wang YC,Li HY,&Zheng XF.(2016).A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment.PLOS ONE,11(11),1-21.
MLA Li YC,et al."A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment".PLOS ONE 11.11(2016):1-21.
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