Fast human whole body motion imitation algorithm for humanoid robots

Abstract

In this paper, we propose a real-time imitation algorithm for humanoid robots to mimic human's eight-chain whole-body motions for the first time. Eight-chain human model is constructed from skeletal data captured by Kinect to represent human whole-body motions, and eight-chain robot model is constructed according to humanoid robot body structures for human motion imitation. First, motion mapping strategy is employed to generate postures of robot by fitting corresponding eight kinematic chains in above two models. The positions of robot's end effectors can be obtained after motion mapping. Then, Inverse Kinematic (IK) algorithm is used to generate joint angles of each joint chain with joint angle limitation. At last, the center of mass is controlled over the support polygon by adjusting ankle joints and hip joints for balance control, and balance analysis is made for each frame to build a stable action. In the post-processing, self-collision avoidance and joint angle speed limitation are employed. In the experiments, the proposed algorithm is tested on humanoid robot NAO, and the results demonstrate that NAO can imitate human's eight-chain motions with a high accuracy in real-time.