Abstract
In this chapter we will describe an artificial visual system for autonomously moving vehicles. The system is able to navigate towards a given target location, whilst avoiding collisions with any obstacles that may be present in the environment. The system is composed of a neural network with several different wiring schemes, giving rise to functionally different parts within this network. The network has been implemented in a two-dimensional, i.e., flat, world using computer simulations.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Baratoff, B., Toepfer, Chr. and Neumann H.: Combined space variant maps for optical-flow-based navigation. Biol Cybern 83, 199–209 (2000)
Franceschini, N., Pichon, J.M. and Blanes, C: From insect vision to robot vision. Phil Trans Roy Soc London B 337, 283–294 (1992)
Glasius, R., Komoda, A. and Gielen, S.C.A.M.: A biologically inspired neural net for trajectory formation and obstacle avoidance. Biol Cybern 84, 511–520 (1996)
Mastebroek, H.A.K., Zaagman, W.H. and Lenting, B.P.M.: Movement detection: performance of a wide-field element in the visual system of the blowfly. Vis Res 20, 467–474 (1980)
Möller, R.: Insect visual homing strategies in a robot with analog processing. Biol Cybern 83, 231–243 (2000)
Mulder, E. and Mastebroek, H.A.K.: Construction of an interactive and competitive artificial neural network for the solution of path planning problems. In: ESANN’98. Proceedings of the 6th European Symposium on Artificial Neural Networks (Ed. M. Verleysen), D facto, 407–412 (1998)
Mura, F., Martin, N. and Franceschini, N.: Biologically inspired eye movements for the visually guided navigation of robots. In: ESANN’96. Proceedings of the 4th European Symposium on Artificial Neural Networks (Ed. M. Verleysen), D facto, 135–147 (1996)
Reichardt, W.: Movement perception in insects. In: Processing of optical data by organisms and machines (Ed. W. Reichardt), Academic Press NY, 465–493 (1969)
Valavanis, K.P., Herbert, T., Kolluru, R. and Tsourveloudis, N.: Mobile robot navigation in 2-D using an electrostatic potential field. IEEE trans on systems, man and cybernetics 30, 187–197 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Mulder, E., Mastebroek, H.A. (2001). Path Planning and Obstacle Avoidance using a Recurrent Neural Network. In: Mastebroek, H.A.K., Vos, J.E. (eds) Plausible Neural Networks for Biological Modelling. Mathematical Modelling: Theory and Applications, vol 13. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0674-3_11
Download citation
DOI: https://doi.org/10.1007/978-94-010-0674-3_11
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-3864-5
Online ISBN: 978-94-010-0674-3
eBook Packages: Springer Book Archive