Self-Adapting Modular Robotics: A Generalized Distributed Consensus Framework

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Self-Adapting Modular Robotics: A Generalized Distributed Consensus Framework

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Title: Self-Adapting Modular Robotics: A Generalized Distributed Consensus Framework
Author: Yu, Chih-Han; Nagpal, Radhika

Note: Order does not necessarily reflect citation order of authors.

Citation: Yu, Chih-Han and Radhika Nagpal. 2009. Self-adapting modular robotics: A generalized distributed consensus framework. In Robotics and Automation, 2009. ICRA '09. IEEE International Conference on, May 12-17, 2009, Kobe, Japan, 1881-1888. Piscataway, N.J.: Institute of Electrical and Electronics Engineers.
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Abstract: Biological systems achieve amazing adaptive behavior with local agents performing simple sensing and actions. Modular robots with similar properties can potentially achieve self-adaptation tasks robustly. Inspired by this principle, we present a generalized distributed consensus framework for selfadaptation tasks in modular robotics. We demonstrate that a variety of modular robotic systems and tasks can be formulated within such a framework, including (1) an adaptive column that can adapt to external force, (2) a modular gripper that can manipulate fragile objects, and (3) a modular tetrahedral robot that can locomote towards a light source. We also show that control algorithms derived from this framework are provably correct. In real robot experiments, we demonstrate that such a control scheme is robust towards real world sensing and actuation noise. This framework can potentially be applied to a wide range of distributed robotics applications.
Published Version: doi:10.1109/ROBOT.2009.5152663
Other Sources: http://www.eecs.harvard.edu/ssr/papers/icra09-yu.pdf
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.163.1815&rep=rep1&type=pdf
http://dl.acm.org/citation.cfm?id=1703942
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:5360186

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  • FAS Scholarly Articles [7470]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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