Abstract
Biped robots are expected to be able to operate in a human living environment. It is necessary to generate autonomous walking, such as avoiding and overcoming obstacles to adapting to various environments with and maintaining stability. The walking behavior of biped robots is determined by the landing point coordinates and the time of each support period. Optimization using genetic algorithms can derive the optimal walking motion based on minimizing energy consumption and walking time with stability. The purpose of this study is to generate biped robot gait including obstacle avoidance motion. The genetic algorithm optimization used to generate a straight walking motion is extended and applied to generate a turning motion. The waist trajectory is made into a three-dimensional curve to smooth the connection between each gait and reduce energy consumption. Assuming that the walking environment with obstacles has been identified, the effectiveness of this method is demonstrated by the results of generating turning motions for several environments.
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