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Paper WeB03.1

Hudson, Nicolas (Jet Propulsion Laboratory), Howard, Tom (Jet Propulsion Laboratory), Ma, Jeremy (Jet Propulsion Laboratory), Jain, Abhinandan (Jet Propulsion Laboratory), Bajracharya, Max (JPL), Myint, Steven (Jet Propulsion Laboratory), Matthies, Larry (Jet Propulsion Laboratory), Backes, Paul (Jet Propulsion Laboratory), Hebert, Paul (California Institute of Technology), Fuchs, Thomas (California Institute of Technology), Burdick, Joel (California Institute of Technology)

End-To-End Dexterous Manipulation with Deliberate Interactive Estimation

Scheduled for presentation during the Regular Session "Grasping: Learning and Estimation" (WeB03), Wednesday, May 16, 2012, 10:30−10:45, Meeting Room 3 (Mak'to)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on February 24, 2018

Keywords Dexterous Manipulation, Motion Control of Manipulators, Behavior-Based Systems

Abstract

This paper presents a model based approach to autonomous dexterous manipulation, developed as part of the DARPA Autonomous Robotic Manipulation (ARM) program. The developed autonomy system uses robot, object, and environment models to identify and localize objects, and well as plan and execute required manipulation tasks. Deliberate interaction with objects and the environment increases system knowledge about the combined robot and environmental state, enabling high precision tasks such as key insertion to be performed in a consistent framework. This approach has been demonstrated across a wide range of manipulation tasks, and is the leading manipulation approach in independent DARPA testing.

 

 

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