Model-based autonomous system for performing dexterous, human-level manipulation tasks
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10514_2013_Article_9371.pdf
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Author(s) • • • • • • • • •
Hudson, Nicolas
Ma, Jeremy
Hebert, Paul
Jain, Abhinandan
Bajracharya, Max
Allen, Thomas
Sharan, Rangoli
Horowitz, Matanya
Kuo, Calvin
Matthies, Larry
Date Issued
November 2013
Journal
Autonomous Robots
Publisher
Springer US
Citation
Hudson, Nicolas et al. “Model-Based Autonomous System for Performing Dexterous, Human-Level Manipulation Tasks.” Autonomous Robots 36.1–2 (2014): 31–49.
Version
Author's final manuscript
Abstract
This article presents a model based approach to autonomous dexterous manipulation, developed as part of the DARPA Autonomous Robotic Manipulation Software (ARM-S) program. Performing human-level manipulation tasks is achieved through a novel combination of perception in uncertain environments, precise tool use, forceful dual-arm planning and control, persistent environmental tracking, and task level verification. Deliberate interaction with the environment is incorporated into planning and control strategies, which, when coupled with world estimation, allows for refinement of models and precise manipulation. The system takes advantage of sensory feedback immediately with little open-loop execution, attempting true autonomous reasoning and multi-step sequencing that adapts in the face of changing and uncertain environments. A tire change scenario utilizing human tools, discussed throughout the article, is used to described the system approach. A second scenario of cutting a wire is also presented, and is used to illustrate system component reuse and generality.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1007/s10514-013-9371-y