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A simple local navigation system inspired by hippocampal function and its autonomous mobile robot implementation

Miki T., Hayashi H., Goto Y., Watanabe M., Inoue T.

Journal of Automation Mobile Robotics and Intelligent Systems

2010

Vol. 4, No. 2

31-38

We propose a practical simple local navigation system inspired by the sequence learning mechanism of the entorhino-hippocampal system. The proposed system memorizes a route as sequences of landmarks in the same way humans do. The proposed local navigation system includes a local route memory unit, landmark extraction unit, and learning-type matching unit. In the local route memory unit, the concept of the sequence learning mechanism of the entorhino-hippocampal system is implemented using a fully connected network, while a sequence of landmarks is embedded in the connection matrix as the local route memory. This system has two operation modes: learning and recall modes. In learning mode, a sequence of landmarks, i.e. a local route, is represented by enhanced loop connections in the connection matrix. In recall mode, the system traces the stored route comparing current landmarks with the stored landmarks using the landmark extraction and learning-type matching units. The system uses a prospective sequence to match the current landmark sequence with the recalled one. Using a prospective sequence in the route comparison allows confirmation of the correct route and deals with any slight change in the current sequence of landmarks. A certainty index is also introduced for judging the validity of the route selection. We describe a basic update mechanism for the stored landmark sequence in the case of a small change in the local route memory. The validity of the proposed system is confirmed using an autonomous mobile robot with the proposed navigation system.