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Paper FrA11.3

Yu, Chih-Han (Harvard University), Nagpal, Radhika (Harvard University)

Self-Adapting Modular Robotics: A Generalized Distributed Consensus Framework

Scheduled for presentation during the Regular Sessions "Biologically-Inspired Robots - I" (FrA11), Friday, May 15, 2009, 09:10−09:30, Room: 503

2009 IEEE International Conference on Robotics and Automation, May 12 - 17, 2009, Kobe, Japan

This information is tentative and subject to change. Compiled on January 24, 2022

Keywords Cellular and Modular Robots, Biologically-Inspired Robots, Distributed Robot Systems

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 self-adaptation 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.

 

 

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