Vision-based leader-follower formations with limited information

Hyeun Jeong Min, Andrew Drenner, Nikolaos Papanikolopoulos

Research output: Contribution to journalConference articlepeer-review

18 Scopus citations

Abstract

This paper presents a new vision-based leaderfollower formation algorithm where the leader's trajectory is unknown to the robots which are following. Formation schemes in straight lines and diagonal formations are introduced which are both stable and observable in the presence of limited views. The algorithms are novel since they only use local image measurements through a pinhole camera to estimate the leader's position. This approach does not require specialized markings nor extensive robot communications. The algorithms are also decentralized. We apply an input-output feedback linearization for system stability and utilize an Extended Kalman Filter (EKF) for estimation. Simulations illustrate how the proposed formation controls work. Real experiments utilizing multiple miniature robots are also presented and illustrate the challenges associated with noisy images in real-world applications.

Original languageEnglish (US)
Article number5152261
Pages (from-to)351-356
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
DOIs
StatePublished - 2009
Event2009 IEEE International Conference on Robotics and Automation, ICRA '09 - Kobe, Japan
Duration: May 12 2009May 17 2009

Bibliographical note

Funding Information:
VI. ACKNOWLEDGEMENTS This material is based upon work supported in part by, the U. S. Army Research Laboratory and the U. S. Army Research Office under contract number #911NF-08-1-0463 (Proposal 55111-CI), and the National Science Foundation through grants #IIS-0219863, #CNS-0224363, #CNS-0324864, #CNS-0420836, #IIP-0443945, #IIP-0726109, and #CNS-0708344.

Publisher Copyright:
© 2009 IEEE.

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