From object categories to grasp transfer using probabilistic reasoning

Marianna Madry, Dan Song, Danica Kragic
2012 2012 IEEE International Conference on Robotics and Automation  
In this paper we address the problem of grasp generation and grasp transfer between objects using categorical knowledge. The system is built upon an i) active scene segmentation module, able of generating object hypotheses and segmenting them from the background in real time, ii) object categorization system using integration of 2D and 3D cues, and iii) probabilistic grasp reasoning system. Individual object hypotheses are first generated, categorized and then used as the input to a grasp
more » ... tion and transfer system that encodes task, object and action properties. The experimental evaluation compares individual 2D and 3D categorization approaches with the integrated system, and it demonstrates the usefulness of the categorization in task-based grasping and grasp transfer.
doi:10.1109/icra.2012.6225052 dblp:conf/icra/MadrySK12 fatcat:mzdfu3lz6nb7vfuov26zgdjfi4