Published February 21, 2007 | Version 15955
Journal article Open

Predictive Model of Sensor Readings for a Mobile Robot

Authors/Creators

Description

This paper presents a predictive model of sensor readings for mobile robot. The model predicts sensor readings for given time horizon based on current sensor readings and velocities of wheels assumed for this horizon. Similar models for such anticipation have been proposed in the literature. The novelty of the model presented in the paper comes from the fact that its structure takes into account physical phenomena and is not just a black box, for example a neural network. From this point of view it may be regarded as a semi-phenomenological model. The model is developed for the Khepera robot, but after certain modifications, it may be applied for any robot with distance sensors such as infrared or ultrasonic sensors.

Files

15955.pdf

Files (567.1 kB)

Name Size Download all
md5:4b2631d38cd1da0dc52bbbe6fa7c0e19
567.1 kB Preview Download

Additional details

References

  • <p>
  • Breitenberg, V.: Vehicles: Experiments in Synthetic Psychology. MIT, Cambridge, MA (1984).
  • T. Duckett, U. Nehmzow, Learning to predict sonar readings for mobile robot landmark selection, Internal Report, University of Manchester, Manchester, UK, 1999.
  • Fleischer, J., Marsland, S., Shapiro, J., Sensory anticipation for autonomous selection of robot landmarks, M. Butz et al. (Eds.): Anticipatory Behavior ..., LNAI 2684, pp. 201-221, Springer-Verlag 2003.
  • Khepera 2, User Manual, K-Team, S.A. 2001, http://ftp.k-team.com/khepera/documentation/Kh2UserManual.pdf
  • Marsland, S., Nehmzow, U., and Duckett, T. (2001). Learning to select distinctive landmarks for mobile robot navigation. Robotics and Autonomous Systems, 37:241-260.
  • Tani, J.: Model-based learning for mobile robot navigation from the dynamical systems perspective. IEEE Trans. Syst. Man Cybern., Part B, Cybern. 26(3), 421-436 (1996).</p>