Research on virtual human running autonomous devices based on cyclic-coordinate descent algorithm

Abstract

The traditional virtual human running research method completes the motion analysis under the ideal state, which lead to cannot obtain the accurate kinematic stability and the coincidence rate of the trajectory curve of the gravity center. To address these problems, the virtual human running research method based on cyclic-coordinate descent (CCD) algorithm is proposed in this paper. The skeleton driver is constructed based on CCD algorithm and the virtual human skeleton model is built. The running state of virtual human is analyzed through multi-joint movement, and the constraint equation of virtual human running is constructed to realize the data simulation of the running movement of virtual human. By using the skeleton model and constraint equation, the kinematics of virtual human is solved. The gravity center trajectory is calculated by using matrix transpose algorithm. Combining with the virtual human upper body movement and the parameters extraction of specified path running, the research of virtual human running based on CCD algorithm is realized. Experimental result show that the proposed virtual human running method improves the kinematic stability by 45.81% compared with the traditional method, and the coincidence rate of the gravity center trajectory is increased by 63.42%.