Pose Determination of a Grasped Object Using Limited Sensing

摘要

This report explores methods for determining the pose of a grasped object usingonly limited sensor information. The problem of pose determination is to find the position of an object relative to the hand. The information is useful when grasped objects are being manipulated. The problem is hard because of the large space of grasp configurations and the large amount of uncertainty inherent in dexterous hand control. By studying limited sensing approaches, the problem's inherent constraints can be better understood. This understanding helps to show how additional sensor data can be used to make recognition methods more effective and robust. This report introduces three approaches for pose determination. The first is based on an interpretation tree representation of possible object feature placements on finger segments. The tree is built in real-time based on the hand's configuration and an object model. The method is highly efficient as it only explores consistent paths through the tree.... Robotics Haptics, Recognition, Pose determination, Hands.