An auto-adaptable algorithm to generate human-like locomotion for different humanoid robots based on motion capture data

Abstract

The work presented in this paper deals with the generation of trajectories for humanoid robots imitating human gaits captured with a motion capture system. Once the human motion is recorded, this one is modified to be adapted to the robot morphology. The proposed method could be used for human-like robots of different sizes and masses. The generated gaits are closed to the human's ones while respecting the robot balance and the floor contacts. First the human joint angles are computed from the markers coordinates and applied directly to the robot kinematics model. Then, from this non-corrected motion, the trajectories of both feet and of the Zero Moment Point (ZMP) are generated respecting the constraints of floor contact and balance control. From this data, an inverse kinematic algorithm is used to compute the joint angles of the robot according to the feet and ZMP trajectories. The results with the robot HRP-2 (AIST, Kawada Industries, Inc) and the small-sized humanoid HOAP-3 (Fujitsu Automation Ltd) are compared with the human motion.