期刊
FRONTIERS IN NEURAL CIRCUITS
卷 15, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fncir.2021.743888
关键词
legged robot; locomotion control; frequency adaptation; motor pattern adaptation; central pattern generator
Existing adaptive locomotion control mechanisms for legged robots are typically focused on individual types of adaptation and are seldom combined. This work introduces a CPG-based locomotion controller integrating both frequency and motor pattern adaptation mechanisms, resulting in high energy efficiency and precision in locomotion. The combination of frequency and motor pattern mechanisms shows promise for further studies on adaptive locomotion control.
Existing adaptive locomotion control mechanisms for legged robots are usually aimed at one specific type of adaptation and rarely combined with others. Adaptive mechanisms thus stay at a conceptual level without their coupling effect with other mechanisms being investigated. However, we hypothesize that the combination of adaptation mechanisms can be exploited for enhanced and more efficient locomotion control as in biological systems. Therefore, in this work, we present a central pattern generator (CPG) based locomotion controller integrating both a frequency and motor pattern adaptation mechanisms. We use the state-of-the-art Dual Integral Learner for frequency adaptation, which can automatically and quickly adapt the CPG frequency, enabling the entire motor pattern or output signal of the CPG to be followed at a proper high frequency with low tracking error. Consequently, the legged robot can move with high energy efficiency and perform the generated locomotion with high precision. The versatile state-of-the-art CPG-RBF network is used as a motor pattern adaptation mechanism. Using this network, the motor patterns or joint trajectories can be adapted to fit the robot's morphology and perform sensorimotor integration enabling online motor pattern adaptation based on sensory feedback. The results show that the two adaptation mechanisms can be combined for adaptive locomotion control of a hexapod robot in a complex environment. Using the CPG-RBF network for motor pattern adaptation, the hexapod learned basic straight forward walking, steering, and step climbing. In general, the frequency and motor pattern mechanisms complement each other well and their combination can be seen as an essential step toward further studies on adaptive locomotion control.
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