Efficiency energy on humanoid robot walking using evolutionary algorithm

One of the problems in humanoid locomotion generation is energy efficiency. This paper proposes a method for energy efficiency optimization in simple humanoid robot locomotion using single objective genetic algorithm. With the aim to produce walking trajectory system using minimum energy and good stabilization, torque and oscillation analysis are required to calculate the stabilization. The number of desired outputs in this system is 4 parameters and the number of inputs is 9 parameters. We used neural network with back propagation learning mechanism to realize the relationship between input and output data as well as producing fitness function for genetic algorithm. The trajectory system has 2 trajectory equations, which is pelvis trajectory and ankle trajectory. Ankle trajectory is formed from circle function in Cartesian coordinate space and pelvis trajectory is formed from third order polynomial equation. Both of them are influenced by inclination of robot body. In the experiment, we apply this system using Bioloid robot with inertial sensor already installed. The experimental results show the analysis of energy by observing the torque resulted by servomotor in each joint. We observe that using this system, the torque value resulted by servomotors was decreased and has good stabilization.