A behavior control strategy of the hexapod robots based on a virtual motoneuron network was proposed, in order to improve the adaptability and behavior ability of legged robots. By simulating the biological neural-muscle control mechanism, a behavioral motor neural control architecture for a legged robot was constructed, which could process the external environment information, adjust the neural signal intensity, obtain the signal processing and behavioral response mechanism similar to animals, realize the quickly response of the robot to the environment and the adaptive adjustment of the robot body and legs. Experiments results showed that the proposed mechanism made the intensity of neural signals automatically adjust with environmental changes. The strong adaptability to the environment and the behavioral diversity of the robot were verified.
基于虚拟运动神经网络的六足机器人行为控制<007机器人>
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