Gait learning method for quadrupedal robot based on subjective human feeling

In the field of pet robots and robot-assisted therapy (RAT), characterization of animal motion is important for the development of robots resembling various animals. This paper presents a method for the generation of animal gait in quadrupedal robots. In this study, we employed AIBO as an experimental quadrupedal robot and generated the gait of the robot on the basis of an animal´s gait. First, we optimized the mono-leg orbit, which can efficiently output a propulsive force, by imitating a dog´s gait using a genetic algorithm. Moreover, we generated the quadrupedal gait of AIBO using both the optimum orbit of the mono-leg and an animal´s gait, classified as the gait of a walking dog based on zoology. Furthermore, we administered a questionnaire study to determine subjective human feelings to choose the best gait for AIBO from among the various gaits mentioned above. Finally, minor deviation of parameters for each joint was corrected to realize the stable gait on the ground.