Trapezoidal fuzzy control for locomotion of bipedal robot on uneven environments

This paper describes the design methodology of a trapezoidal fuzzy control for bipedal robot to improve the locomotion stability on uneven terrain environments. The membership functions for the proposed control were designed based on empirical data. These data were utilized to create possibility histograms which is converted into trapezoidal fuzzy control. The force sensor was implemented to generate the center of pressure position feedback to evaluate the robot's walking stability. To measure the robot's tilt posture for locomotion stability improvement, the IMU sensor was implemented. Then, two trapezoidal fuzzy control further modifies the gait and posture of the robot by generating appropriate offset angles. Meta learner is applied to combine the results of the fuzzy control to generate the final offset angles of joints. The performance of the proposed control scheme was simulated and verified on MATLAB environment with 21 DOF bipedal robot. The results demonstrated ability of the proposed control scheme to control the bipedal robot on uneven environment with slope surface.