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A Comparison of Decision Making Criteria and Optimization Methods for Active Robotic Sensing

  • Lyudmila Mihaylova
  • Tine Lefebvre
  • Herman Bruyninckx
  • Klaas Gadeyne
  • Joris De Schutter
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2542)

Abstract

This work presents a comparison of decision making criteria and optimization methods for active sensing in robotics. Active sensing incorporates the following aspects: (i ) where to position sensors, and (ii ) how to make decisions for next actions, in order to maximize information gain and minimize costs. We concentrate on the second aspect: “Where should the robot move at the next time step?”. Pros and cons of the most often used statistical decision making strategies are discussed. Simulation results from a new multisine approach for active sensing of a nonholonomic mobile robot are given.

Keywords

Mobile Robot Information Gain Relative Entropy Markov Decision Process Task Execution 
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 2003

Authors and Affiliations

  • Lyudmila Mihaylova
    • 1
  • Tine Lefebvre
    • 1
  • Herman Bruyninckx
    • 1
  • Klaas Gadeyne
    • 1
  • Joris De Schutter
    • 1
  1. 1.Katholieke Universiteit LeuvenHeverleeBelgium

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