神经科学
退缩反射
仿人机器人
反射
尖峰神经网络
感觉系统
计算机科学
人工智能
伤害
神经形态工程学
机器人
人工神经网络
心理学
医学
受体
内科学
作者
Fengyi Wang,J. Rogelio Guadarrama-Olvera,Nitish V. Thakor,Gordon Cheng
标识
DOI:10.1109/lra.2023.3268624
摘要
In this letter, we present a method for realizing the heat-evoked nociceptive withdrawal reflex (NWR) in the upper limb of a humanoid robot so that it can avoid the potential damage caused by noxious heat. We use a spiking neural network whose structure, encoding scheme, and form of information transmission mimic the reflex arc in humans to improve bio-plausibility. The proper synaptic strengths between the sensory neurons and the interneurons in the first two layers are learned using the bio-plausible reward-modulated spike timing-dependent plasticity learning algorithm. By monitoring the spikes from the motor neuron in the third layer, a reflex matching the intensity of the stimulation can be evoked. Experimental evaluations show that noxious heat stimulation can be detected online and evoke the NWR. The experiments on a full-size humanoid robot show that the method enables robots to avoid potential damage robustly with proper NWR, depending on the site and intensity of the stimulation. We also verify that the method takes advantage of the intrinsic characteristics of its neuromorphic encoding scheme to reproduce essential features of the NWR, e.g., spatial summation effect and temporal summation effect in humans. The improved bio-plausibility and the capability to reproduce the human-like feature.
科研通智能强力驱动
Strongly Powered by AbleSci AI