Abstract: To develop a new navigation method with bio-inspired spatial representation and autonomous positioning ability, a model of spatial representation and location estimation based on place cells is presented in this paper. In the proposed model, the place cells of self-motion perception are generated through the transformation from grid cells to place cells based on radial basis function (RBF) neural network. Simultaneously, the place cells of visual perception are generated through environment perception and similar measure. Finally, the above two kinds of place cells are fused by information weighting, and the place cells of multi-information perception are generated to represent the explored space. When the vehicle runs in the represented space, it can realize autonomous positioning by processing the firing activity of population place cells based on gravity center estimation principle. Simulation results indicate the proposed model can represent the explored space, and the firing characteristic of the generated place cells is similar to that of biological place cells. Besides, when there is an error in one of the perception modes, the spatial representation of multi-information perception can also give the good location estimation performance.

Key words: bionic positioning, spatial representation, place cells, multi-information perception