Self-adapting modular robotics: A generalized distributed consensus framework

Chih Han Yu, Radhika Nagpal

Research output: Contribution to journalConference articlepeer-review

39 Scopus citations

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.

Original languageEnglish (US)
Article number5152663
Pages (from-to)1881-1888
Number of pages8
JournalProceedings - IEEE International Conference on Robotics and Automation
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE International Conference on Robotics and Automation, ICRA '09 - Kobe, Japan
Duration: May 12 2009May 17 2009

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Self-adapting modular robotics: A generalized distributed consensus framework'. Together they form a unique fingerprint.

Cite this