Dynamic balance of humanoid robot using pose classification with incremental proportional derivative dead-zone control

In the beginning, a dynamic sensing system including the hardware and the low-pass and Kalman filtering is designed. It is then installed at the center of gravity (CoG) of the humanoid robot (HR) and can capture the responses of the pitch and roll axes during the execution of specific task. After the analytic design, a set of desired pitch and roll trajectory for a specific task is achieved. In addition, the 3D coordinates of four tips (i.e., two hands and feet) with respect to the neck and waist centers of HR are computed by the kinematics of 4-DoFs of two arms and 6-DoFs of two legs. Based on these 3D coordinate, the total 36 classes are achieved. Without measuring the contact force of two feet, without unnecessarily interfering the original task, the incremental proportion-derivative dead-zone control of the pitch and roll directions for each class is designed by the control of different suitable motors. It is cost-effective as compared with other methods. Finally, the experiments of continuous walking motion in the presence of external disturbances are presented to evaluate the effectiveness and robustness of the proposed method.