Virtual human hybrid control in virtual assembly and maintenance simulation

To improve virtual human motion simulation and generation efficiency in virtual assembly and maintenance (A&M) environment, based on a detailed analysis of virtual human control methods in A&M simulation, a virtual human hybrid control method is presented in this paper. In the proposed method, virtual human A&M motion is divided into three types: primitive motion (PM), fine motion (FM) and transitional motion (TM). For PM, a real operator can drive a virtual human in real time for A&M operation via virtual reality interactive devices; in this way, the PM can be quickly generated. As for FM and TM generation, their semantic-level parameterized models including engineering attributes are created; then, their generation processes are represented; in the generation processes, a virtual human posture automatic reasoning model is established to support auto-generating A&M motion. The approaches in the present study are validated by generating virtual human motions in partial assembly process of auto engine. Results show that the proposed method can improve A&M motion simulation efficiency and support the fast generation of realistic A&M motion.