Submission Deadline: July 10, 2026
Cognitive Integration of Manned and Unmanned Systems based on Brain-inspired Intelligence Under Complex Scenarios
复杂场景下基于类脑智能的有人-无人认知共融
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| Xinyu Zhang |
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| Northwestern Polytechnical University, China |
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| Topics: |
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- Precise evaluation of multi-modal cognitive states and intention analysis in human-computer interaction (人机交互中的多模态认知状态精准评估与意图解析)
- Brain-inspired intelligence and autonomous decision-making for unmanned systems in high dynamic scenarios (面向高动态场景的类脑智能与无人系统自主决策)
- Dynamic alignment mechanism of human-machine intention for collaboration (有人-无人协同中的人机意图动态对齐机制)
- Human-machine shared control and dynamic authority allocation (人机共享控制与动态权限分配)
- Trust and interpretability modeling in human-machine hybrid intelligent systems (人机混合智能系统中的信任与可解释性建模)
- Application and verification of human-unmanned cluster cognitive fusion system (有人-无人集群认知共融系统的应用与验证)
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| Summary: |
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- With the deep deployment of unmanned equipment in complex and high-dynamic environments such as aerospace, the traditional one-way command-based human-machine interaction mode often leads to cognitive overload for operators and insufficient adaptive capacity for the system. To address this issue, this special track explores how to achieve bidirectional dynamic adaptation of human-machine intent relying on brain-inspired intelligence, promoting the system to leap from physical synergy to deep cognitive integration. This track targets experts and scholars in the interdisciplinary field of artificial intelligence, cognitive science, and human factors engineering. It aims to condense the core theoretical framework of dynamic alignment of human-machine intent through interdisciplinary in-depth discussions, explore a scientific evaluation system for multimodal physiology and behavior, and ultimately provide a practical technical path and design idea for building a safe, robust, and efficient new generation of human-machine hybrid intelligent system.
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- 随着无人装备在航空航天等复杂高动态环境中的深度部署，传统单向指令式的人机交互模式常导致操作人员认知超负荷及系统自适应能力不足。针对此瓶颈，本专题将探讨如何依托类脑智能实现人机意图的双向动态适应，推动系统向深层的认知共融跃升。本专题面向人工智能、认知科学与人因工程交叉领域的专家学者，旨在通过跨学科深度研讨，凝练人机意图动态对齐的核心理论框架，探索多模态生理与行为的科学评估体系；最终为构建安全、鲁棒且高效的新一代人机混合智能系统，提供切实可行的技术路径与设计思路。
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