Robot formations using a single camera and entropy-based segmentation

Hyeun Jeong Min, Nikolaos Papanikolopoulos

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


This work presents a new problem along with our new algorithm for a multi-robot formation with minimally controlled conditions. For multi-robot cooperation, there have traditionally been prevailing assumptions in order to collect the necessary information. These assumptions include the existence of communication systems among the robots or the use of specialized sensors such as laser scanners or omnidirectional cameras. However, they are not always valid, especially in emergency situations or with miniature robots. We, therefore, need to deal with the conditions that have received less attention in research regarding a multi-robot formation. There are several challenges: (1) less information is available than the well-known formation algorithms assume, (2) following strategies for deformable shapes in a formation with only local information available are needed, and (3) target segmentation without any markers is required. This work presents a formation algorithm based on a visual tracking algorithm, including how to process the image measurements provided by a single monocular camera. Through several experiments with real robots (developed at the University of Minnesota), we show that the proposed algorithms work well with minimal sensing information.

Original languageEnglish (US)
Pages (from-to)21-41
Number of pages21
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Issue number1
StatePublished - Sep 2012

Bibliographical note

Funding Information:
Acknowledgements We would like to thank the anonymous reviewers for their time and thoughtful comments. 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 #911NF-08-1-0463 (Proposal 55111-CI) and the National Science Foundation through grants #CNS-0324864, #CNS-0420836, #IIP-0443945, #IIP-0726109, #CNS-0708344, #CNS-0821474, and #IIP-0934327.


  • Entropy
  • Moving target segmentation
  • Robot formations
  • Robot tracking


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