Grasping arbitrarily shaped 3-D objects from a pile

Abstract

Presents a reliable and robust approach to the problem of grasping arbitrarily shaped 3-D objects from a pile. The approach adheres to the paradigm of purposive vision, which says that one should only extract as much information as it is needed to perform a certain task, e.g. grasping, while a complete and precise recovery of the shape of the objects is not necessary. The authors show that planar patches obtained by the recover-and-select paradigm contain enough information to enable generating object hypotheses and to estimate grasping points for the objects. The authors present some results for objects with polyhedral as well as with curved surfaces obtained on real range images.