（VC，虚拟专辑）是推动学科开放学术交流的创新出版形式。区别于传统专刊，VC 打破传统专刊模式的固有局限，围绕特定主题开展定向征稿与专题归集，鼓励全球科研人员以更灵活、多元的方式开展学术合作，共同搭建高水平学术交流与资源共享平台!
Virtual Collection (VC) 4.0
Control and Decision Intelligence for Unmanned Systems
Call for papers’ fields
Unmanned systems (USs) are undergoing a profound transformation—from "algorithmic capability enhancement" toward "paradigmatic reconstruction." As a core driving force of this transformation, the convergence of artificial intelligence, data science, and sensor networks is giving rise to novel research paradigms. The central focus of US research is shifting from merely "enabling autonomous operation" to building resilient unmanned systems capable of operating reliably under uncertainty, disturbance, and adversarial conditions. At the same time, the relationship between humans and unmanned systems has entered a new phase of "human-machine symbiosis." These shifts present unprecedented opportunities and challenges for both theoretical inquiry and practical applications, from understanding the cooperative control and decision-making of heterogeneous USs to developing governance frameworks that ensure safety, robustness, and trustworthiness.
This Virtual Collection focuses on the intersection of control theory, artificial intelligence, and decision intelligence for unmanned systems, with particular emphasis on paradigmatic innovations, computational methodologies, and system-level frameworks that address the complexities of autonomous operation in uncertain and dynamic environments. Advances in data science, artificial intelligence, and sensor networks are driving the continuous evolution and increasing maturity of USs, which operate without an onboard human operator and may be remotely operated, autonomous, or combine both modes. These systems encompass Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), Unmanned Surface Vehicles (USVs), Unmanned Underwater Vehicles (UUVs), and satellites. These systems are not only redefining technological paradigms but also extending human operational reach into once-inaccessible environments—from the deep oceans to outer space—and are pivotal in major strategic needs such as scientific discovery and defense security, including space exploration, earth observation, and underwater exploration, while also playing a crucial role in economic and social development, such as logistics and environmental monitoring.
The research landscape of USs is undergoing a paradigm shift, with increasing emphasis on several cutting-edge directions. Key topics include cooperative control and decision-making for heterogeneous USs; real-time optimal control, planning, and decision-making; embodied intelligence and bio-inspired systems that integrate environmental perception, adaptive movement, and intelligent responses to replicate biological advantages; distributed intelligence for US platforms, enabling consensus-based control and game-theoretic strategies to enhance system scalability; AI-driven situational awareness and predictive analysis; and safety, fault tolerance, anti-interference, operational robustness, resilience, and trustworthy AI for US platforms, with a focus on resilient control and fault-tolerant operation, as well as explainable and trustworthy artificial intelligence. The Collection aims to bring together recent advances in theoretical frameworks, algorithmic approaches, and application-driven studies, thereby promoting the transition of US research from isolated algorithmic development toward integrated, scalable, and trustworthy unmanned systems, and providing a scientific basis for deploying USs in strategic domains such as space exploration, earth observation, underwater exploration, logistics, and environmental monitoring.
VC Scope
This Virtual Collection aims to bring together breakthrough research across the following areas (Cover but not limited to):
1. Cooperative Control and Decision-making for USs
● USs Modeling and Simulation
● Cooperative control of heterogeneous USs
● Real-time optimal control, planning, and decision making for USs
● Explainability and Interpretability in Cooperative Control
● Perception–control integration for autonomous exploration
2. Embodied Intelligence and Bio-inspired Unmanned Systems
● Integration of Swarm Intelligence and Evolutionary Computation in Unmanned Systems
● Bio-inspired Perception and Multimodal Perception Fusion
● Bio-inspired Motion Control and Flight Mechanisms
● Autonomous Learning and Lifelong Adaptation in Unmanned Systems
● Perception–Action Integrated Intelligence in Unmanned Systems
3. Distributed Intelligence for Unmanned Systems
● Consensus-based control and game-theoretic strategies
● Formation flight and swarm control
● Edge computing and cloud–edge collaborative architectures
● Population games and game learning
● Federated learning for unmanned systems
4. Unmanned Systems in the Era of Big Data and Artificial Intelligence
● Multi-source data fusion and analytics for autonomous perception and control
● Generative AI in Cooperative Systems
● Large Language Model (LLM) and Vision Language Model (VLM) assisted Cooperative Systems
● Edge AI and distributed learning for resource-constrained unmanned platforms
● Data-driven behavioral prediction and intent recognition for unmanned systems
● Vision-Based Autonomous Navigation and Environmental Understanding for USs
● Robust Visual SLAM and Localization in Complex or Extreme Environments
● Cross-Modal Sensing Integration for Reliable Perception (Vision + LiDAR/IMU/Sonar)
● Benchmarking and Evaluation Methodologies for Vision-Centric Unmanned Systems
5. Safety, Robustness and Trustworthiness of Unmanned Systems
● Fault Detection and Health Monitoring for Unmanned Systems
● Predictive Maintenance and Reliability Management in Long-Endurance Unmanned Platforms
● Robust and Safe Learning for Unmanned Systems in Uncertain Environments
● Formal Verification and Safety Assurance of Autonomous Decision-Making Systems
● Explainable and Trustworthy Artificial Intelligence for Autonomous Control and Monitoring
● Resilient Control and Fault-Tolerant Operation of Multiple Unmanned Systems
6. Unmanned Systems for Space, Air, Ground and Sea
● On-orbit serving and frontier exploration of unmanned space systems
● Cluster collaboration and intelligent interaction of unmanned aerial systems
● Control and integration of unmanned ground systems
● Precise operations of unmanned systems in underground spaces
● Marine applications and underwater technologies of unmanned systems
7. Unmanned Systems for Economic and Social Development
● Unmanned Systems for Urban Air Mobility and Smart Logistics
● Precision Agriculture and Automated Resource Management via Unmanned Systems
● Environmental Monitoring and Climate Analytics with Unmanned Platforms
● Unmanned Systems for Emergency Response and Disaster Relief
● Unmanned Systems for Critical Infrastructure Inspection and Maintenance
VC Host
1
（Guanghui Zhou）
教授
中国科学院大学经济与管理学院教授，博士生导师。研究领域包括运营管理、优化与决策、信息系统工程等交叉学科，主要聚焦物流与供应链管理、航空航天任务规划与管理。主持承担国家重点研发计划、国家自然科学基金重大研究计划、国家自然科学基金面上项目等国家级项目10余项。研究成果发表于European Journal of Operational Research、IEEE Transactions on Systems, Man, and Cybernetics: Systems、IEEE Transactions on Intelligent Transportation Systems、Transportation Research Part E: Logistics and Transportation Review，International Journal of Production Economics，Computers & Operations Research，ENGINEERING Management，Fundamental Research，《系统工程理论与实践》《中国管理科学》《管理评论》等国内外期刊等国内外期刊。担任 Editorial Board。
2
（Xin Zhao）
教授
北京科技大学计算机与通信工程学院教授，博士生导师。研究领域包括计算机视觉、模式识别、数据中心人工智能（Data-centric AI）、AI4Science。在 IEEE TPAMI、IJCV、CVPR、NeurIPS、ICCV、AAAI 等国际顶级期刊与会议发表学术论文多篇，出版专著 Visual Object Tracking: An Evaluation Perspective（Springer Nature, 2025）。担任 Pattern Recognition (PR) 期刊副主编、International Journal of Computer Vision (IJCV) 特刊首席客座编辑、Pattern Recognition 特刊首席客座编辑，并多次组织 CVPR、ICCV 等顶级会议 Workshop 与 Tutorial。
3
（Junge Zhang）
研究员
中国科学院自动化研究所研究员，博士生导师，中国科学院特聘核心岗位研究员。研究领域包括博弈智能、强化学习、智能体（RL agent and LLM agent）、多智能体、大模型推理、AI4Science。入选中国科学院青年促进会优秀会员、中国科学院稳定支持基础研究青年团队、北京市科技新星。课题组主要围绕复杂系统博弈智能及其跨学科应用开展研究，与国家能源、国家电投、国家电网、航天科技、华为等单位保持长期合作。
4
（Yang Zhang）
高级工程师
工学博士，中国科学院空天信息创新研究院高级工程师、硕士生导师，中国科学院青年创新促进会会员。长期从事低轨星座设计及导航控制、低轨星座地面及演示验证技术研究及系统研制；担任中国科学院青促会信息与管理分会委员、宇航学报、系统仿真学报等期刊青年编委、中国指控学会建模与仿真专委会及中国仿真学会复杂系统建模与仿真专委会委员等；先后主持和参与北斗重大专项、国家重点研发计划、国家自然基金、军委科技委、中科院国防创新及院所合作等多个课题/项目，发表学术论文20余篇；获第五届全国轨道设计大赛一等奖、第八届中国研究生未来飞行器创新大赛二等奖和第十二届国际探测轨迹优化大赛亚军。
4
（Shiyu Hu）
博士后
新加坡南洋理工大学物理与数学科学学院博士后，合作导师为 Kang Hao Cheong 副教授。研究领域包括开放世界视觉、多模态推理、以人为中心的智能体与 AI 教育，核心关注 AI 能力在开放交互环境中的可靠性建模、测量与诊断。在 IEEE TPAMI、IJCV、NeurIPS、ICCV、CVPR、AAAI、ICLR、ACL、Nature 等国际顶级期刊与会议发表学术论文多篇，出版专著 Visual Object Tracking: An Evaluation Perspective（Springer Nature, 2025）。担任 Innovation and Emerging Technologies 副主编、Electronics 特刊客座编辑，并多次在 IJCAI、ECAI、SMC、ICIP、ICPR、ACCV 等国际会议组织 Tutorial。曾获 ICML 2026 Reviewer Award、IEEE SMCS TEAM Program Award、CVPR 2024 Workshop 最佳论文提名等荣誉。
For Authors
Submission Deadline: June 30, 2027.
Submission Online:
https://mc03.manuscriptcentral.com/innovation-inform
Submission Instructions: Please clearly indicate at the end of the Cover Letter that “This manuscript is submitted to the Control and Decision Intelligence for Unmanned Systems and will be collected in this collection upon acceptance.”
Virtual Collection Official Website:
https://www.the-innovation.org/the-innovation-informatics/unmanned-systems
Call for papers’ types
Publication Standard: Rigorously follows the same peer review, editorial, and publishing standards of The Innovation Informatics.
Promotion: Each article, upon formal publication, will be promoted through major domestic and international media channels. In addition, all published articles will be collected into this Virtual Collection and presented on The Innovation Informatics official website via a dedicated webpage.
Contact | 联系
[email protected]
Call for Papers
2026前沿科学创新大会会议通知
2026创新信息学论坛会议通知
创办新刊
September 28, 2026
September 29, 2026
September 30, 2026
October 21, 2026
On the way
On the way
On the way