Robot simulated navigation method based on rat brain-hippocampal navigation

Abstract

The invention discloses a robot simulated navigation method based on rat brain-hippocampal navigation, and belongs to the technical field of robot motion navigation. The method is characterized by that a robot CPU (Central Processing Unit) predefines a grid cell layer cell layer G and a place cell layer P by imitating rat brain and hippocampal tissues, motion information including a motion direction phi and a velocity v is collected when a robot explores an environment, the collected motion information is input into the grid cell layer, the motion information is integrated by using a shock interference model in the grid cell layer to form a grid cell layer response, a connection weight value W of the grid cell layer cell layer G and a place cell layer P is calculated by using a neural network algorithm to form a location cell-grid cell response network, and the robot perception for a space namely is stored in the form of a neural network response. The robot controls a motion decision module to implement motion decision-making according to space information stored in a cognitive map, and the navigation method disclosed by the invention independently obtains a better spatial cognitive effect during an exploration motion of the robot, and can be applied to industrial robots, service robots and the like.

Description

Technical field: [0001] The invention relates to a bionic navigation method for a robot based on the hippocampus structure of the mouse brain and its operating mechanism. The method can be used for autonomous learning of spatial information and for mobile robot autonomous navigation systems or devices facing indoor, street and other environments. Background technique: [0002] An intelligent mobile robot is a robot system that can perceive itself and the environment through sensors, and can move autonomously towards the target in the environment to complete certain functions. When the mobile robot is in an unknown environment, the robot has only little prior knowledge based on the environment, so the cognition of the environment is the most basic prerequisite for autonomous navigation control such as positioning, path planning, and environment modeling. Research on the cognitive ability of humans and animals to the environment, the perception of space and the behavior of sp...

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Problems solved by technology

However, the disadvantage of this model is that it only simulates the environmental cognition process of mice from the perspective of behavior, and does not conform to the anatomical structure and neurophysiological characteristics of the mouse brain. Gerald M Edelman, Jeffrey L.Krichmar and Douglas A.Nitz in 2008 Invented a mobile robot with a simulated hippocampal area in 2010. The mobile robot has a simulated nervous system that simulates the hippocampal area of ​​the brain. It can partly recognize the environment space and memorize segmented environmental navigation information with bionics. The above two methods have higher requirements on the hardware system.

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