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A hybrid approach to fast and accurate localization for legged robots

Published online by Cambridge University Press:  01 November 2008

Renato Samperio ,
Huosheng Hu ,
Francisco Martín  and
Vicente Matellán
Renato Samperio*
Affiliation:
Department of Computing & Electronic Systems, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, United Kingdom
Huosheng Hu
Affiliation:
Department of Computing & Electronic Systems, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, United Kingdom
Francisco Martín
Affiliation:
Robotics Lab-GSyC, DITTE-ESCET-URJC, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain
Vicente Matellán
Affiliation:
Robotics Lab-GSyC, DITTE-ESCET-URJC, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain
*
*Corresponding author. E-mail: renatosamperio@gmail.com
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Summary

This paper describes a hybrid approach to a fast and accurate localization method for legged robots based on Fuzzy-Markov (FM) and Extended Kalman Filters (EKF). Both FM and EKF techniques have been used in robot localization and exhibit different characteristics in terms of processing time, convergence, and accuracy. We propose a Fuzzy-Markov–Kalman (FM–EKF) localization method as a combined solution for a poor predictable platform such as Sony Aibo walking robots. The experimental results show the performance of EKF, FM, and FM-EKF in a localization task with simple movements, combined behaviors, and kidnapped situations. An overhead tracking system was adopted to provide a ground truth to verify the performance of the proposed method.

Keywords

Legged robotsrobot localisationExtended Kalman filtersFuzzy-Markov methods

Information

Type
Article
Information
Robotica , Volume 26 , Issue 6 , November 2008 , pp. 817 - 830
Copyright
Copyright © Cambridge University Press 2008

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