DocumentCode :
237802
Title :
Object recognition and localization for robust grasping with a dexterous gripper in the context of container unloading
Author :
Vaskevicius, Narunas ; Mueller, Christian A. ; Bonilla, M. ; Tincani, Vinicio ; Stoyanov, Todor ; Fantoni, Gualtiero ; Pathak, K. ; Lilienthal, Achim ; Bicchi, A. ; Birk, Andreas
Author_Institution :
Robot. Group, Jacobs Univ. Bremen, Bremen, Germany
fYear :
2014
fDate :
18-22 Aug. 2014
Firstpage :
1270
Lastpage :
1277
Abstract :
The work presented here is embedded in research on an industrial application scenario, namely autonomous shipping-container unloading, which has several challenging constraints: the scene is very cluttered, objects can be much larger than in common table-top scenarios; the perception must be highly robust, while being as fast as possible. These contradicting goals force a compromise between speed and accuracy. In this work, we investigate a state of the art perception system integrated with a dexterous gripper. In particular, we are interested in pose estimation errors from the recognition module and whether these errors can be handled by the abilities of the gripper.
Keywords :
containers; control engineering computing; dexterous manipulators; goods distribution; grippers; industrial robots; logistics; object recognition; autonomous shipping-container unloading; dexterous gripper; object recognition; perception system; pose estimation errors; table-top scenarios; Educational institutions; Grasping; Grippers; Robot sensing systems; Thumb;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation Science and Engineering (CASE), 2014 IEEE International Conference on
Conference_Location :
Taipei
Type :
conf
DOI :
10.1109/CoASE.2014.6899490
Filename :
6899490
Link To Document :
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