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Navigating with a Focus-Directed Mapping Network

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Abstract

This paper considers the problem of environment-mapping for autonomous mobile agents. Central to this problem is how the structure of the external environment can be captured and represented so that an agent is able to autonomously navigate in a robust way. This is an issue that is not clear even given a perfect sensor system that provides all information that the agent needs. Biological data reveal that the activation of hippocampal place cells in an animal, which is performing navigational tasks, is highly correlated with the animal's location, and the sensory basis of place cell firing is of multiple modalities which include landmark detection. As a functional approximation to hippocampal place learning, this paper presents a dynamic network that can be used by an autonomous agent to map landmarks, places and the spatial relation between them. The spatial relation is encoded by embedding an areal coordinate coding principle into the inter-cell connection structure. For the network to be used to map a large space, a focusing mechanism is introduced, which not only constrains the scope of the network in which learning can take place, but also limits the computation needed to the part of the network that is currently relevant to the activity of the agent. This focusing mechanism can also be used to direct dynamic route-finding in the network that the agent builds. Simulation results of the network demonstrate its applicability and computational characteristics.

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Authors and Affiliations

  1. Department of Computer Engineering, Chalmers University of Technology, S-412 96, Gothenburg, Sweden

    Guang Li & Bertil Svenson

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  1. Guang Li
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  2. Bertil Svenson
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Li, G., Svenson, B. Navigating with a Focus-Directed Mapping Network. Autonomous Robots 7, 9–30 (1999). https://doi.org/10.1023/A:1008961628456

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