Vision-based leader-follower formations with limited information

  • Authors:

  • Hyeun Jeong Min;Andrew Drenner;Nikolaos Papanikolopoulos

  • Affiliations:

  • Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN;Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN;Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN

  • Venue:
  • ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
  • Year:
  • 2009

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Abstract

This paper presents a new vision-based leader-follower 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.