公开(公告)号：US20240160221A1

公开(公告)日：2024-05-16

申请号：US18412459

申请日：2024-01-12

Applicant: BEIJING UNIVERSITY OF TECHNOLOGY

Inventor： Naigong Yu ,  Yishen Liao ,  Zongxia Wang ,  Hejie Yu ,  Jianjun Yu ,  Xudong Liu ,  Ruihua Wang

IPC: G05D1/243 ,  G06V20/50

CPC classification number: G05D1/2435 ,  G06V20/50 ,  G05D2105/87

Abstract: A method for constructing episodic memory model based on rat brain visual pathway and entorhinal-hippocampal structure mainly applied to environment cognition and navigation of an intelligent mobile robot to complete tasks of environment cognition map construction and target-oriented navigation is provided. The image information of the environment, the head-direction angle and speed of the robot are collected, and then the head-direction angle and speed of the robot are input into the entorhinal-hippocampal CA3 neural computational model to obtain the robot's precise position. The visual information is input into the computational model of the visual pathway to obtain the scene information in the current vision of the robot. The above two kinds of information are fused and stored in a cognitive node with the topological relationship. Utilizing scenario information to correct the path integration errors during the exploration process of the robot, thereby constructing the episodic cognitive map representing the environment.

公开(公告)号：US20250103051A1

公开(公告)日：2025-03-27

申请号：US18972786

申请日：2024-12-06

Applicant: BEIJING UNIVERSITY OF TECHNOLOGY

Inventor： Naigong Yu ,  Yishen Liao ,  Zongxia Wang ,  Hejie Yu ,  Jianjun Yu ,  Xudong Liu ,  Ruihua Wang

IPC: G05D1/243 ,  G05D1/222 ,  G05D101/15 ,  G05D105/80 ,  G06T7/70

Abstract: A method for constructing episodic memory model based on rat brain visual pathway and entorhinal-hippocampal structure mainly applied to environment cognition and navigation of an intelligent mobile robot to complete tasks of environment cognition map construction and target-oriented navigation is provided. The image information of the environment, the head-direction angle and speed of the robot are collected, and then the head-direction angle and speed of the robot are input into the entorhinal-hippocampal CA3 neural computational model to obtain the robot's precise position. The visual information is input into the computational model of the visual pathway to obtain the scene information in the current vision of the robot. The above two kinds of information are fused and stored in a cognitive node with the topological relationship. Utilizing scenario information to correct the path integration errors during the exploration process of the robot, thereby constructing the episodic cognitive map representing the environment.