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Cooperative Multi-robot Map Merging Using Fast-SLAM

  • N. Ergin Özkucur
  • H. Levent Akın
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5949)

Abstract

Multi-robot map merging is an essential task for cooperative robot navigation. In the realistic case, the robots do not know the initial positions of the others and this adds extra challenges to the problem. Some approaches search transformation parameters using the local maps and some approaches assume the robots will observe each other and use robot to robot observations. This work extends a previous work which is based on EKF-SLAM to the Fast-SLAM algorithm. The robots can observe each other and non-unique landmarks using visual sensors and merge maps by propagating uncertainty. Another contribution is the calibration of noise parameters with supervised data using the Evolutionary Strategies method. The developed algorithms are tested in both simulated and real robot experiments and the improvements and applicability of the developed methods are shown with the results.

Keywords

Belief State Generalize Regression Neural Network Real Robot Experiment Evolutionary Strategy Method Odometry Reading 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • N. Ergin Özkucur
    • 1
  • H. Levent Akın
    • 1
  1. 1.Department of Computer Engineering, Artificial Intelligence LaboratoryBoğaziçi UniversityTurkey

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