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Mobile Bin Picking with an Anthropomorphic Service Robot
In proceedings of IEEE International Conference on Robotics and Automation (ICRA), Mai 2013
Abstract
Grasping individual objects from an unordered pile in a box has been investigated in static scenarios so far. In this paper, we demonstrate bin picking with an anthropomorphic mobile robot. To this end, we extend global navigation techniques by precise local alignment with a transport box. Objects are detected in range images using a shape primitive-based approach. Our approach learns object models from single scans and employs active perception to cope with severe occlusions. Grasps and arm motions are planned in an efficient local multiresolution height map. All components are integrated and evaluated in a bin picking and part delivery task.
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Bibtex
@INPROCEEDINGS{Berner2013,
author = {Nieuwenhuisen, Matthias and Droeschel, David and Holz, Dirk and St{\"u}ckler, Joerg and Berner,
Alexander and Li, Jun and Klein, Reinhard and Behnke, Sven},
title = {Mobile Bin Picking with an Anthropomorphic Service Robot},
journal = {Accepted for IEEE International Conference on Robotics and Automation (ICRA), to appear},
booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
year = {2013},
month = may,
abstract = {Grasping individual objects from an unordered pile in a box has been investigated in static
scenarios so far. In this paper, we demonstrate bin picking with an anthropomorphic mobile robot. To
this end, we extend global navigation techniques by precise local alignment with a transport box.
Objects are detected in range images using a shape primitive-based approach. Our approach learns
object models from single scans and employs active perception to cope with severe occlusions. Grasps
and arm motions are planned in an efficient local multiresolution height map. All components are
integrated and evaluated in a bin picking and part delivery task.}
}