Abstract

Digital human figure models (DHM) are increasingly the tools of choice for assessments of the physical ergonomics of products and workplaces. Software representations of users and workers are used to visualize people performing tasks of interest. Analyses have usually focused on clearance and reach in static postures, not because the actual tasks are static, but rather because DHM have lacked robust, accurate motion simulation capability. Research is underway at many institutions to develop improved motion simulation methods, drawing on a wide variety of methodologies from fields such as computer graphics, kinesiology, motor control, and robotics. Experience in the Human Motion Simulation Laboratory at the University of Michigan suggests that conventional metrics of accuracy for posture and movement prediction do not adequately capture the aspects of human movement that are most important for ergonomic analysis. This paper identifies and justifies a set of these critical features.

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