Scene description for object manipulation in unstructured environments

Abstract

Sensing and reasoning techniques for the data-driven description of objects in unstructured environments are given. One of the techniques presented is for extrapolating the shape of individual objects using symmetries, while the other is applicable to objects jumbled in a pile. No a priori object models are needed for these techniques. A hypothesize and test approach is used to infer complete shape information from range images that represent partial knowledge about an object's shape. Using explicit knowledge about the geometrical relationship of the sensor to the scene, hypotheses are verified to ensure that they do not violate physical laws such as object transparency and solidity. In addition, basic physical rules such as stability and contact are used to improve the estimates of the shapes of objects that may be partially visible or partially outside the field of view of the sensor. >