NDLI: Navigating with an animal brain: a neural network for landmark identification and navigation

Content Provider	IEEE Xplore Digital Library
Author	Gaussier, P. Zrehen, S.
Copyright Year	1994
Description	Author affiliation: ENSEA ETIS, Cergy Pontoise, France (Gaussier, P.)
Abstract	Navigating in an unknown environment is a task commonly accomplished by most animals. Nevertheless, it is not justified to infer that this capacity needs complex reasoning involving abstract geometrical computations. In this paper, the authors' aim is to show that such behavior, including switching between goals, can be simulated by simple artificial neural networks (NN) where no complex computation is performed. The authors present a real development and simulations about a Khepera robot and a simulated system named Prometheus. The authors use a novel neural architecture named PerAc (Perception-Action) which is a systematic way to decompose the control of an autonomous robot in perception and action flows. The authors show that action simplifies the interpretation of perception: each action is a choice and conditions entirely the future of the robot.
Starting Page	399
Ending Page	404
File Size	626478
Page Count	6
File Format	PDF
ISBN	0780321359
DOI	10.1109/IVS.1994.639551
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-10-24
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Navigation Animals Biological neural networks Computational modeling Robots Artificial neural networks Neural networks Computer networks Computer architecture Control systems
Content Type	Text
Resource Type	Article

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