Robot behavior learning system based on striated body structure and learning method thereof

A learning method and learning system technology, applied in the field of robot behavior learning systems, can solve problems that have not yet been seen

Active Publication Date: 2021-03-26
BEIJING UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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  • Robot behavior learning system based on striated body structure and learning method thereof
  • Robot behavior learning system based on striated body structure and learning method thereof
  • Robot behavior learning system based on striated body structure and learning method thereof

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[0054] The present invention will be described in detail below in conjunction with the examples, the purpose is only to better understand the contents of the present invention, therefore, the examples given do not limit the protection scope of the present invention.

[0055] see figure 1 , a structural schematic diagram of a robot behavior learning system based on striatum structure, which includes sensory cortex, motor cortex, hippocampus, thalamus, substantia nigra compacta, ventral tegmental area and striatum. Among them: the activation of place cells in the hippocampus is used for robot positioning. After conducting and processing the olfactory cells and visual cells in the sensory cortex, the robot obtains the corresponding odor energy and obstacle energy in the thalamus. These two energies constitute the current state energy of the robot and are input into the substantia nigra pars compacta and ventral tegmental area. The energy difference between the two states before...

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Abstract

The invention discloses a robot behavior learning system based on a striated body structure and a learning method thereof, and belongs to the technical field of bionics. The robot behavior learning system is composed of sensory cortex, motor cortex, hippocampus, thalamus, a black compact part, an abdominal side quilt area and a striated body, wherein the striated body comprises striated corpusclesand a matrix. The striped corpuscles receive positioning information generated by hippocampus position cells and dopamine information generated by a black compact part and an abdominal covered area,and update orientation information of the robot according to an operation conditioned reflex mechanism. The matrix receives orientation information of the striped corpuscles and performs action selection according to an improved epsilon-greedy algorithm. Behavior habits can be formed after the robot interacts with the environment for a period of time. According to the method, a possible explanation of animal habitual behavior generation is given, and robot autonomous behavior learning can be guided. The method can be applied to the fields of robot navigation, physiology, animal behavioristicsand the like.

Description

technical field [0001] The invention relates to a striatal structure-based robot behavior learning system and a learning method thereof, belonging to the technical field of bionics. Background technique [0002] Behavior learning, such as navigation behavior learning, is one of the key skills of intelligent robots, which embodies the intelligence of robots. Intelligent robots have the ability of cognition and learning, and can optimize their behavior through interaction with the environment, thereby improving the autonomy and adaptability of robots, which is of great significance for replacing humans to complete tasks in disasters or dangerous environments. [0003] Animals can autonomously acquire navigation knowledge and skills through interaction with the environment, simulating the structure and mechanism of animal brains, and endowing them to robots is an important research topic in artificial intelligence and robotics. Many researchers have obtained inspiration from t...

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/0221G05D1/0276
Inventor 阮晓钢柴洁黄静武悦杨贺源朱晓庆李鹏张家辉郭威肖尧
Owner BEIJING UNIV OF TECH
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