Automatically generating humanlike grasp postures of the digital hand is a key issue for the virtual ergonomic assessment of the industrial products. In this paper we propose a new optimization-based approach for generating the realistic grasp posture. As an objective function, we use the number of the contact points, the fit of the specific part of the hand surface for the feature edges of the product surface and the margin for the constraints on the joint angle limits of the figures. The experimental studies on the grasp posture generation for the digital camera indicate that more realistic grasp posture could be generated using the proposed optimization-based method than the one using our former method.
Recently, as handheld information appliances, such as mobile phones, PDAs, have widely spread, the development of these appliances should pay more attention in their ergonomic design. However, the user tests for developing the “ergonomic” appliances are usually done by many real subjects testing a variety of these physical mockups, and the process of these tests usually requires the expensive cost and has to take a long time. So, we propose a software system of an automatic ergonomic assessment system for designing handheld information appliances by integrating the digital hand model with the 3D product model of the appliance. Our system has the following four feature functions for ergonomic assessment: 1) Generation of kinematically and geometrically accurate digital hand models with rich dimensional variation, 2) automatic grasp posture generation and evaluation of the posture stability by estimating the force-closure and the grasp quality, 3) automatic evaluation of ease of the finger motion in operating the user interface, 4) aiding the designers to re-design the housing shapes and user-interfaces in the product model. In this paper we propose a new optimization-based method the 2) of the above functions. As the objective function, we use the number of the contact points, the fit of the specific part of the hand surface for the feature edges of the product surface and the margin for the constraints on the joint angle limits of the figures. The experimental studies on the grasp posture generation for the digital camera indicate that more realistic grasp posture could be generated using the proposed optimization-based method than the one using our former method.
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