Adaptive Landmark-Based Navigation System Using Learning Techniques

  • Bassel Zeidan
  • Sakyasingha Dasgupta
  • Florentin Wörgötter
  • Poramate Manoonpong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8575)

Abstract

The goal-directed navigational ability of animals is an essential prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance navigation, they exploit environmental features, like landmarks, to guide them towards their goal. Inspired by this, we develop an adaptive landmark-based navigation system based on sequential reinforcement learning. In addition, correlation-based learning is also integrated into the system to improve learning performance. The proposed system has been applied to simulated simple wheeled and more complex hexapod robots. As a result, it allows the robots to successfully learn to navigate to distal goals in complex environments.

Keywords

Goal-directed behavior Sequential reinforcement learning Correlation based learning Neural networks Walking robots 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Bassel Zeidan
    • 1
  • Sakyasingha Dasgupta
    • 2
  • Florentin Wörgötter
    • 2
  • Poramate Manoonpong
    • 2
    • 3
  1. 1.Faculty of Mathematics and Computer Science, Institute of Computer ScienceUniversity of GöttingenGöttingenGermany
  2. 2.Bernstein Center for Computational Neuroscience (BCCN)University of GöttingenGöttingenGermany
  3. 3.The Mærsk Mc-Kinney Møller InstituteUniversity of Southern DenmarkOdense MDenmark

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