| A brain-inspired robot pain model based on a spiking neural network | |
Feng, Hui1,2; Zeng, Yi1,2,3,4
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| Source Publication | FRONTIERS IN NEUROROBOTICS
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| ISSN | 1662-5218 |
| 2022-12-20 | |
| Volume | 16Pages:13 |
| Corresponding Author | Zeng, Yi(yi.zeng@ia.ac.cn) |
| Abstract | IntroductionPain is a crucial function for organisms. Building a "Robot Pain" model inspired by organisms' pain could help the robot learn self-preservation and extend longevity. Most previous studies about robots and pain focus on robots interacting with people by recognizing their pain expressions or scenes, or avoiding obstacles by recognizing dangerous objects. Robots do not have human-like pain capacity and cannot adaptively respond to danger. Inspired by the evolutionary mechanisms of pain emergence and the Free Energy Principle (FEP) in the brain, we summarize the neural mechanisms of pain and construct a Brain-inspired Robot Pain Spiking Neural Network (BRP-SNN) with spike-time-dependent-plasticity (STDP) learning rule and population coding method. MethodsThe proposed model can quantify machine injury by detecting the coupling relationship between multi-modality sensory information and generating "robot pain" as an internal state. ResultsWe provide a comparative analysis with the results of neuroscience experiments, showing that our model has biological interpretability. We also successfully tested our model on two tasks with real robots-the alerting actual injury task and the preventing potential injury task. DiscussionOur work has two major contributions: (1) It has positive implications for the integration of pain concepts into robotics in the intelligent robotics field. (2) Our summary of pain's neural mechanisms and the implemented computational simulations provide a new perspective to explore the nature of pain, which has significant value for future pain research in the cognitive neuroscience field. |
| Keyword | brain-inspired intelligent robot robot pain spiking neural network free energy principle spike-time-dependent-plasticity |
| DOI | 10.3389/fnbot.2022.1025338 |
| WOS Keyword | FREE-ENERGY PRINCIPLE ; ANTERIOR CINGULATE ; EXPECTANCY |
| Indexed By | SCI |
| Language | 英语 |
| WOS Research Area | Computer Science ; Robotics ; Neurosciences & Neurology |
| WOS Subject | Computer Science, Artificial Intelligence ; Robotics ; Neurosciences |
| WOS ID | WOS:000905739000001 |
| Publisher | FRONTIERS MEDIA SA |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/51100 |
| Collection | 类脑智能研究中心_类脑认知计算 |
| Corresponding Author | Zeng, Yi |
| Affiliation | 1.Chinese Acad Sci, Inst Automat, Brain inspired Cognit Intelligence Lab, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, Peoples R China 4.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China |
| First Author Affilication | Institute of Automation, Chinese Academy of Sciences |
| Corresponding Author Affilication | Institute of Automation, Chinese Academy of Sciences; Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| Recommended Citation GB/T 7714 | Feng, Hui,Zeng, Yi. A brain-inspired robot pain model based on a spiking neural network[J]. FRONTIERS IN NEUROROBOTICS,2022,16:13. |
| APA | Feng, Hui,&Zeng, Yi.(2022).A brain-inspired robot pain model based on a spiking neural network.FRONTIERS IN NEUROROBOTICS,16,13. |
| MLA | Feng, Hui,et al."A brain-inspired robot pain model based on a spiking neural network".FRONTIERS IN NEUROROBOTICS 16(2022):13. |
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