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A Floating-point Extended Kalman Filter Implementation for Autonomous Mobile Robots

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Abstract

Localization and Mapping are two of the most important capabilities for autonomous mobile robots and have been receiving considerable attention from the scientific computing community over the last 10 years. One of the most efficient methods to address these problems is based on the use of the Extended Kalman Filter (EKF). The EKF simultaneously estimates a model of the environment (map) and the position of the robot based on odometric and exteroceptive sensor information. As this algorithm demands a considerable amount of computation, it is usually executed on high end PCs coupled to the robot. In this work we present an FPGA-based architecture for the EKF algorithm that is capable of processing two-dimensional maps containing up to 1.8 k features at real time (14 Hz), a three-fold improvement over a Pentium M 1.6 GHz, and a 13-fold improvement over an ARM920T 200 MHz. The proposed architecture also consumes only 1.3% of the Pentium and 12.3% of the ARM energy per feature.

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Acknowledgements

The authors would like to thank CAPES (Ref. BEX2683/06–7) and EPSRC (Grant EP/C549481/1 and EP/C512596/1) for the financial support given to develop this research project. We also thank Carlos R.P. Almeida Jr. for his important help to generate the EKF software benchmarks.

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Authors and Affiliations

  1. Institute of Mathematical and Computing Sciences, The University of São Paulo, São Carlos, Brazil

    Vanderlei Bonato & Eduardo Marques

  2. Department of Electrical and Electronic Engineering, Imperial College London, London, UK

    George A. Constantinides

Authors
  1. Vanderlei Bonato
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  2. Eduardo Marques
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  3. George A. Constantinides
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Correspondence to Vanderlei Bonato.

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Bonato, V., Marques, E. & Constantinides, G.A. A Floating-point Extended Kalman Filter Implementation for Autonomous Mobile Robots. J Sign Process Syst Sign Image Video Technol 56, 41–50 (2009). https://doi.org/10.1007/s11265-008-0257-8

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  • DOI: https://doi.org/10.1007/s11265-008-0257-8

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