A neural cognitive heuristic-based dual-system game visual language navigation method and device

By simulating the collaborative mechanism of the brain's habit system and goal-oriented system, the problems of high power consumption and single decision-making in visual language navigation technology are solved, realizing the instant response and improved environmental adaptability of embodied intelligent navigation.

CN122170896AActive Publication Date: 2026-06-09NANJING UNIV OF INFORMATION SCI & TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
NANJING UNIV OF INFORMATION SCI & TECH
Filing Date
2026-05-09
Publication Date
2026-06-09

AI Technical Summary

Technical Problem

Existing visual language navigation technologies suffer from high computational power consumption, limited decision-making capabilities, inference-action delays, and insufficient environmental adaptability, making it difficult to meet the real-time response requirements of embodied intelligent navigation.

Method used

We employ a dual-system game-theoretic visual-language navigation method inspired by neurocognition to simulate the brain's habit system and goal-oriented system. Through multi-brain region collaboration mechanisms and dynamic neurotransmitter balance, we achieve real-time obstacle avoidance and global semantic alignment, construct a cognitive closed-loop link, and simulate the risk response and regulation logic of brain circuits.

Benefits of technology

It significantly improves the environmental adaptability, logical transparency, and all-time-domain navigation robustness of intelligent agents, realizes low-energy dynamic environmental computing resource allocation and decision-making flexibility, and supports highly secure embodied intelligent navigation.

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Abstract

The application discloses a dual-system game visual language navigation method and device based on neural cognitive inspiration, which comprises the following steps: acquiring visual feature information and language feature information, extracting visual feature embedding and text feature embedding, and then performing modal alignment and feature fusion to obtain a current state; inputting a state, an action and a global hidden state of a previous moment into a world model based on a gated recurrent unit to generate a current global hidden state; based on the current state and the current global hidden state, based on a multi-brain region collaborative mechanism, generating initial activation tendencies of a goal-oriented system and a habit system by using a prefrontal cortex and a sensory motor cortex, calculating dynamic interest functions of the goal-oriented system and the habit system by using a precingulate gyrus, a thalamus and a premotor cortex, arbitrating and selecting an execution system according to the initial activation tendencies and the dynamic interest functions of the goal-oriented system and the habit system, generating a current execution action by using the execution system, and feeding back and adjusting.
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