Adaptive Static Balance of a Biped Robot Using Neural Networks
نویسنده
چکیده
keywords: adaptive control, biped walking, learning control, neural networks An adaptive static balance scheme was implemented on an experimental biped. The control scheme used pre-planned but adaptive motion sequences in combination with closed loop reactive control. CMAC neural networks were responsible for the adaptive control of side-to-side and front-to-back balance. Qualitative and quantitative test results show that the biped performance improved with neural network training. The biped is able to start and stop on demand, and to walk with continuous motion on flat surfaces at a rate of up to 2.2 steps per minute, with up to 12 cm long strides.
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