Date of Degree
MS (Master of Science)
Electrical and Computer Engineering
The role of digital humans in product design and assessment is ever increasing. Accurate digital human models are used to provide feedback on virtual prototypes of products, thus reducing costs and shortening the design cycle. An essential part of product assessment in the virtual world is the ability of the human model to interact correctly and naturally with the product model. This involves reaching, grasping and manipulation. This work addresses the difficult problem of grasp planning for digital humans. We develop a semi-interactive system for synthesizing grasps based on the object's shape, and implement this system for SantosTM, the digital human developed at the Virtual Soldier Research Program at the University of Iowa. The system is composed of three main parts: First, a shape matching module that creates an initial power grasp for the object based on a database of pre-calculated grasps. Second, an optimization based module provides control of the fingertip locations. This can be used to synthesize precision grasps under the user's guidance. Finally, a grasp quality module provides feedback about the grasp's mechanical stability. The novelty of our approach lies in the fact that it takes into consideration the upper body posture when planning the grasp, so the whole arm and the torso are involved in the grasp.
Posture Prediction, synthetic actors, power grasps, shape matching, digital manikins, grasp synthesis
Copyright 2007 Faisal Amer Goussous