DocumentCode :
2040662
Title :
Uncertainty reduction using dynamics
Author :
Moll, Mark ; Erdmann, Michael A.
Author_Institution :
Dept. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
Volume :
4
fYear :
2000
fDate :
2000
Firstpage :
3673
Abstract :
For assembly tasks parts often have to be oriented before they can be put in an assembly. We present a new approach to parts orienting through the manipulation of pose distributions. Through dynamic simulation we can determine the pose distribution for an object being dropped from an arbitrary height on an arbitrary surface. By varying the drop height and the shape of the support surface we can find the initial conditions that will result in a pose distribution with minimal entropy. We attempt to uniquely orient a part with high probability just by varying the initial conditions. We derive a condition on the pose and velocity of an object in contact with a sloped surface that will allow us to quickly determine the final resting configuration of the object. This condition can then be used to quickly compute the pose distribution. We also show simulation and experimental results which confirm that our dynamic simulator can be used to find the true pose distribution of an object
Keywords :
assembling; dynamics; minimum entropy methods; probability; production control; assembly; dynamics; minimal entropy; parts feeding; pose distribution; probability; Assembly; Belts; Computational modeling; Computer science; Distributed computing; Entropy; Gravity; Robots; Shape; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on
Conference_Location :
San Francisco, CA
ISSN :
1050-4729
Print_ISBN :
0-7803-5886-4
Type :
conf
DOI :
10.1109/ROBOT.2000.845304
Filename :
845304
Link To Document :
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