A Vision-Based Formation Control Framework

Loading...
Thumbnail Image
Penn collection
Departmental Papers (MEAM)
General Robotics, Automation, Sensing and Perception Laboratory
Degree type
Discipline
Subject
GRASP
Engineering
Mechanical Engineering
Funder
Grant number
License
Copyright date
Distributor
Related resources
Author
Das, Aveek K.
Fierro, Rafael
Ostrowski, James P.
Spletzer, John
Contributor
Abstract

We describe a framework for cooperative control of a group of nonholonomic mobile robots that allows us to build complex systems from simple controllers and estimators. The resultant modular approach is attractive because of the potential for reusability. Our approach to composition also guarantees stability and convergence in a wide range of tasks. There are two key features in our approach: 1) a paradigm for switching between simple decentralized controllers that allows for changes in formation; 2) the use of information from a single type of sensor, an omnidirectional camera, for all our controllers. We describe estimators that abstract the sensory information at different levels, enabling both decentralized and centralized cooperative control. Our results include numerical simulations and experiments using a testbed consisting of three nonholonomic robots.

Advisor
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Publication date
2002-10-01
Journal title
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Suggested Citation: Das, Aveek K. et al. (2002). A Vision-Based Formation Control Framework. IEEE Transactions on Robotics and Automation, Vol. 18(5). p. 813-825. ©2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Recommended citation
Collection