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Optimization of cooperative motion for humanoid robots using a genetic algorithm

Humanoid robots usually consist of a number of joint actuators. Thus, it is essential to adequately control the torques of the joint actuators for achieving desirable motion. Also, torque profile needs to be properly generated especially when a robot is to be moved in cooperation with external environment. For the purpose, this paper proposed a method of optimizing humanoid-robot cooperative motion using a genetic algorithm to find an optimized posture in consideration of torque distribution. An eighteen degree-of-freedom humanoid robot was adopted in this study, and a motion pushing an object was considered. When the robot pushing an object moves from a position to one of the next candidate positions, the torques for all joints were calculated. Then, the torques obtained was reflected to an objective function, which was to be minimized by a genetic algorithm. Here, the objective function was designed in such a way that the surplus torques for all joints should be maximized. As a result of successive minimization processes, a posture optimized for the cooperative motion was found. To show the effectiveness of the proposed method, a series of simulations were carried out for a humanoid robot, and the results were analyzed. The simulation results show that the proposed method can be extended to the control of torques for humanoid robots cooperative with external environment.