A Method of Spatial Place Representation Based on Biological Place Cells Firing

LI Weilong; WU Dewei; ZHOU Yang; DU Jia

doi:10.11999/JEIT151331

Volume 38 Issue 8

Sep. 2016

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LI Weilong, WU Dewei, ZHOU Yang, DU Jia. A Method of Spatial Place Representation Based on Biological Place Cells Firing[J]. Journal of Electronics & Information Technology, 2016, 38(8): 2040-2046. doi: 10.11999/JEIT151331

Citation:

LI Weilong, WU Dewei, ZHOU Yang, DU Jia. A Method of Spatial Place Representation Based on Biological Place Cells Firing[J]. Journal of Electronics & Information Technology, 2016, 38(8): 2040-2046. doi: 10.11999/JEIT151331

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A Method of Spatial Place Representation Based on Biological Place Cells Firing

doi: 10.11999/JEIT151331

1.
(Information and Navigation College, Air Force Engineering University, Xi&rsquo
2.

Funds:

The National Natural Science Foundation of China (61273048)

Received Date: 2015-11-26
Rev Recd Date: 2016-04-18
Publish Date: 2016-08-19

Abstract

Abstract

In order to realize intelligent and autonomous navigation of vehicles, a method of spatial place representation based on biological place cells firing is proposed. A relationship is built that the spatial location of vehicle is corresponding with the distances between the vehicle and different landmarks, and a map of place cells is constructed in two different ways of space coverage. Then using the real-time distances sensed inspires place cells firing so as to estimate the location of the vehicle. An analysis is carried out about different parameters in the model influence on spatial location expression and the performance of positioning. The simulation results show that both two ways can realize location expression and autonomous positioning through using the map of place cells. The way that the space is separated equally is influenced by the distance interval greatly, and the way of building the map of place cells through exploring randomly, starting off with the perspective of sensing spatial location autonomously, can finish spatial location expression and autonomous positioning better through choosing appropriate interval and trained time.
- Autonomous navigation,
- Biological positioning,
- Spatial representation,
- Place cell

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References(18)

References

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