Air-ground cooperation system and air-ground cooperation method based on own intelligence

Through the Vision-Language-Action (VLA) framework, the multimodal data fusion and intelligent decision-making of drones and unmanned vehicles are realized, solving the problem of insufficient perception and interaction capabilities of existing systems in complex environments, and improving the task execution efficiency and robustness of collaborative systems.

CN120560232APending Publication Date: 2025-08-29NANJING UNIV
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Patent Information

Application Number
CN202510680159.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-26
Publication Date
2025-08-29

AI Technical Summary

Technical Problem

The existing UAV and UAV collaboration systems have insufficient multimodal perception capabilities in complex environments, limited natural language interaction capabilities, low dynamic collaboration efficiency, and poor algorithm generalization, making it difficult to achieve cross-platform adaptation.

Method used

Using the Vision-Language-Action (VLA) framework, the natural language instructions and visual information are analyzed through the embodied intelligent unit, and multi-modal data is integrated to realize cross-modal data fusion and intelligent decision-making, dynamic task allocation and execution.

Benefits of technology

It improves the mission execution capabilities of drones and unmanned vehicles in complex environments, enhances multimodal perception and natural language interaction capabilities, and ensures the system's collaboration and robustness in complex environments.

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Abstract

The invention discloses an air-ground cooperation system and an air-ground cooperation method based on intelligence, and relates to the field of intelligent unmanned system control. The system comprises an intelligent unit, a multi-element sensing unit, a communication unit and a task execution unit. Based on a Vision-Language-Action (VLA) framework, an intelligent unit with a body realizes end-to-end analysis of a natural language instruction and a visual instruction, fuses sensing data of an unmanned aerial vehicle and an unmanned vehicle, generates a joint feature code with time-space alignment, and dynamically allocates a cooperative task. The communication unit supports low-delay end-to-end communication and real-time data synchronization between clusters, and ensures efficient interaction between agents. The multi-element sensing unit is integrated with a visual camera, a laser radar and high-precision positioning equipment, and air-ground environment multi-mode sensing is achieved. And the task execution unit supports the unmanned aerial vehicle to complete coordination actions in a complex scene. According to the scheme, the problems of insufficient multi-mode perception, limited natural language interaction and low dynamic cooperation efficiency of the existing system are solved, and the cooperation capability and system robustness of the unmanned aerial vehicle and the unmanned aerial vehicle in a complex environment are remarkably improved.
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