A Bionic Simultaneous Location and Mapping with Closed-Loop Correction Based on Dynamic Recognition Threshold

A bionic simultaneous location and mapping with closed-loop correction based on the dynamic recognition threshold is proposed to solve the problem that there exist missing matching and false matching in the model of the rat simultaneous location and mapping for the continuous experienced scenes in the bio-inspired navigation. An enhanced threshold factor and an attenuated threshold factor are introduced in the stage of forming local view cells. The recognition results for the first few frames are used as the excitation to dynamically adjust the template recognition threshold of the current frame image in real time, and to judge whether new local view cells need to generate according to the threshold. Then the experience map is corrected through closed loop detection by integrating the recognition results for the continuous experienced scenes. Experimental results and a comparison with the method under the fixed threshold show that the proposed method not only avoids false matching, but also increases the correct recognition rate, which urges the agent to modify the experience map in a timely manner and to improve the accuracy of the experience map.