Automatic optimization model for virtual human's working behaviors

Simulation of humanoid adaptive behaviors is a prerequisite of ergonomic evaluation. To overcome the shortages of existing technologies, an autonomic optimization model of virtual human's working behaviors is presented based on multi-agent cooperative games. In this model, the humanoid adaptive behaviors in working environment is defined as multi-objective optimization problem, and the definitions of mannequin workspace and behavior elements are proposed for discretization of human behaviors. A simulation algorithm based on fuzzy multi-objective games theory is presented to solve this model. With fuzzy multi-objective Nash negotiation theory, a grads-up method is adopted to search the Pareto optimizing solutions of human's working posture. Case studies show that the human's comfortable working posture can be derived by the new strategy even in cases with only insufficient data and better adaptability of the method in engineering domain can be reached. © 2012 ISCAS.