Skip to main content
SpringerLink
Log in

GA-Based Search for Paths with Minimum Energy Consumption for Mobile Robot Systems

  • Conference paper
  • First Online:
Computational Intelligence. Theory and Applications (Fuzzy Days 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2206))

Included in the following conference series:

Abstract

A GA based path planning software for mobile robot systems focussing on energy consumption is presented. One special feature of this software is the consideration of changing texture — and therefore changing energy requirements when moving — within given environments. Problem specific genetic operators are introduced, and especially the handling of exceptional situations is described in detail.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baker, J.E.: Reducing Bias and Inefficiency in the Selection Algorithm. Genetic Algorithms and their Applications: Proc. 2nd Intl. Conference on Genetic Algorithms. Lawrence Erlbaum Associations, Hillsdale, NJ, 1987

    Google Scholar 

  2. Gerke, M.: Genetische Bahnplanung für mobile Roboter. 8. Workshop Fuzzy-Control des GMA-FA 5.22. Dortmund, 1998

    Google Scholar 

  3. Lee, S., Kardaras, G.: Collision-Free Path Planning with Neural Networks. Proc. 1997 IEEE Intl. Conference on Robotics and Automation. Albuquerque, NM, 1997

    Google Scholar 

  4. Löffler, A., Mondada, F., Rieckert, U., editors: Experiments with the Mini-Robot Khepera. Proc. 1st International Khepera Workshop. Paderborn, 1999

    Google Scholar 

  5. Xiao, J., Michalewicz, Z., Zhang, L., Trojanowski, K.: Adaptive Evolutionary Planner/Navigator for Mobile Robots. IEEE Transactions on Evolutionary Computation, 1(1), 1997

    Google Scholar 

  6. Zhao, M., Ansari, N., Hou, E.S.H.: Mobile Manipulator Path Planning by a Genetic Algorithm. Journal of Robotic Systems, 11(3), 1994

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Fernuniversität Hagen, 58084, Hagen, Germany

    Marcus Gemeinder & Michael Gerke

Authors
  1. Marcus Gemeinder
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael Gerke
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Computer Science I, University of Dortmund, 44221, Dortmund, Germany

    Bernd Reusch

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gemeinder, M., Gerke, M. (2001). GA-Based Search for Paths with Minimum Energy Consumption for Mobile Robot Systems. In: Reusch, B. (eds) Computational Intelligence. Theory and Applications. Fuzzy Days 2001. Lecture Notes in Computer Science, vol 2206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45493-4_60

Download citation

  • DOI: https://doi.org/10.1007/3-540-45493-4_60

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42732-2

  • Online ISBN: 978-3-540-45493-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation