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59383 |
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|a Nangeroni, Paul
|e author
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|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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|a Hsiao, Kaijen
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|a Hsiao, Kaijen
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|a Huber, Manfred
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|a Saxena, Ashutosh
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|a Ng, Andrew Y.
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|a Hsiao, Kaijen
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|a Reactive Grasping Using Optical Proximity Sensors
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|b Institute of Electrical and Electronics Engineers,
|c 2010-10-15T18:39:33Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/59383
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|a We propose a system for improving grasping using fingertip optical proximity sensors that allows us to perform online grasp adjustments to an initial grasp point without requiring premature object contact or regrasping strategies. We present novel optical proximity sensors that fit inside the fingertips of a Barrett Hand, and demonstrate their use alongside a probabilistic model for robustly combining sensor readings and a hierarchical reactive controller for improving grasps online. This system can be used to complement existing grasp planning algorithms, or be used in more interactive settings where a human indicates the location of objects. Finally, we perform a series of experiments using a Barrett hand equipped with our sensors to grasp a variety of common objects with mixed geometries and surface textures.
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|a United States. Defense Advanced Research Projects Agency (transfer learning program under contract number FA8750- 05-2-0249)
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|a Willow Garage (Firm)
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|a en_US
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|a Article
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|t IEEE International Conference on Robotics and Automation, 2009. ICRA '09
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