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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第9期8卷 4249-4262页

作者： Xu, Wei Dai, Xingyuan Zhao, Chen Tang, Yiqing Cheng, Jie Qu, Zhiyou Zhang, Tao Lv, Yisheng Macau Univ Sci & Technol Fac Innovat Engn Taipa 999078 Macau Peoples R China China Acad Railway Sci Signal & Commun Res Inst Beijing 100081 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China North Automat Control Technol Inst Taiyuan 030006 Peoples R China

The centralized traffic control (CTC) system of intelligent railways plays a vital role in implementing railway dispatching, improving transportation efficiency, and ensuring train safety. However, with the development of high-speed railways (HSRs), the construction of new lines and the upgrading of existing equipment have become increasingly prevalent, posing significant challenges to the safety and reliability of the CTC system. To address these challenges, this article proposes a scenario-driven parallel testing method for the CTC system. We use divisible and combinable scenarios to describe the functionality and processes of testing. Building upon the scenario representation, a virtual-real interactive testing method is adopted, where virtual testing is employed to generate a large number of scenarios simultaneously, thereby accelerating the testing process of the CTC system while ensuring comprehensive testing coverage. Field testing is carried out to validate the reliability of the CTC system in real operational environments, particularly in critical scenarios. The CTC parallel testing system has been deployed in multiple railway bureaus in China, and the deployment results demonstrate that parallel testing can improve testing efficiency, alleviate tester workload, augment the proficiency of on-site construction, and boost the stability and reliability of CTC systems.

关键词： Centralized traffic control high-speed railway systems intelligent testing parallel intelligence artificial intelligence railway dispatching systems

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A Multilayer and Multimodal-Fusion Architecture for Simultaneous Recognition of Endovascular Manipulations and Assessment of Technical Skills

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IEEE TRANSACTIONS ON CYBERNETICS 2022年第4期52卷 2565-2577页

作者： Zhou, Xiao-Hu Xie, Xiao-Liang Feng, Zhen-Qiu Hou, Zeng-Guang Bian, Gui-Bin Li, Rui-Qi Ni, Zhen-Liang Liu, Shi-Qi Zhou, Yan-Jie Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Ctr Excellence Brain Sci & Intelligence Technol Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China

The clinical success of the percutaneous coronary intervention (PCI) is highly dependent on endovascular manipulation skills and dexterous manipulation strategies of interventionalists. However, the analysis of endovascular manipulations and related discussion for technical skill assessment are limited. In this study, a multilayer and multimodal-fusion architecture is proposed to recognize six typical endovascular manipulations. The synchronously acquired multimodal motion signals from ten subjects are used as the inputs of the architecture independently. Six classification-based and two rule-based fusion algorithms are evaluated for performance comparisons. The recognition metrics under the determined architecture are further used to assess technical skills. The experimental results indicate that the proposed architecture can achieve the overall accuracy of 96.41%, much higher than that of a single-layer recognition architecture (92.85%). In addition, the multimodal fusion brings significant performance improvement in comparison with single-modal schemes. Furthermore, the K-means-based skill assessment can obtain an accuracy of 95% to cluster the attempts made by different skill-level groups. These hopeful results indicate the great possibility of the architecture to facilitate clinical skill assessment and skill learning.

关键词： Endovascular manipulations multilayer and multimodal-fusion architecture (MMFA) percutaneous coronary intervention (PCI) technical skill assessment

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AirVista: Empowering UAVs with 3D Spatial Reasoning Abilities Through a Multimodal Large Language Model Agent

AirVista: Empowering UAVs with 3D Spatial Reasoning Abilitie...

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International Conference on Intelligent Transportation

作者： Fei Lin Yonglin Tian Yunzhe Wang Tengchao Zhang Xinyuan Zhang Fei-Yue Wang Department of Engineering Science Faculty of Innovation Engineering Macau University of Science and Technology Macau China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China Capital University of Economics and Business Beijing China Department of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

In urban environments, complex transportation demands, including land, air, and maritime transport, are increasingly growing. While significant advancements have been made in land transportation and autonomous driving, research on urban air mobility (UAM) systems is still in its early stages. This paper presents an innovative urban air unmanned aerial vehicle (UAV) framework: AirVista, which is designed and built based on the Artificial systems, Computational experiments, and Parallel execution (ACP) approach, integrated with a multimodal large language model (MLLM) agent. Considering that UAM tasks often require UAVs to possess fine-grained spatial perception and reasoning capabilities, and given that existing MLLMs are somewhat lacking in exploring 3D spaces, this paper further proposes an instruction fine-tuning strategy integrated with 3D spatial knowledge, which has been validated experimentally for its effectiveness. Additionally, to enhance the understanding of the efficiency of MLLM for UAV tasks, this paper delves into prompt fine-tuning templates tailored for UAV task decomposition. Through experimental demonstrations, we showcase that the prompt-tuned MLLM exhibits efficient task decomposition and execution capabilities in handling complex UAV tasks.

关键词： Three-dimensional displays Large language models Urban areas Land transportation Autonomous aerial vehicles Cognition Space exploration Planning

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Discrete-Time Self-Learning Parallel control

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2022年第1期52卷 192-204页

作者： Wei, Qinglai Wang, Lingxiao Lu, Jingwei Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Qingdao Acad Intelligent Ind Parallel Intelligence Innovat Ctr Qingdao 266109 Peoples R China

In this article, a new self-learning parallel control method, which is based on adaptive dynamic programming (ADP) technique, is developed for solving the optimal control problem of discrete- time time-varying nonlinear systems. It aims to obtain an approximate optimal control law sequence and simultaneously guarantees the convergence of the value function. Establishing the time-varying artificial system by neural networks in a certain time-horizon, a control-sequence-improvement ADP algorithm is developed to obtain the control law sequence. For the first time, the criteria of the parallel execution are presented, such that the value function is proven to converge to a finite neighborhood of the optimal performance index function. Finally, numerical results and analysis are presented to demonstrate the effectiveness of the parallel control method.

关键词： Optimal control Nonlinear systems Time-varying systems Performance analysis complex systems Biological neural networks ACP adaptive dynamic programming (ADP) approximate dynamic programming nonlinear systems optimal control parallel control reinforcement learning

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Development of an Untethered Adaptive Thumb Exoskeleton for Delicate Rehabilitation Assistance

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IEEE TRANSACTIONS ON ROBOTICS 2022年第6期38卷 3514-3529页

作者： Li, Guotao Cheng, Long Gao, Ziwen Xia, Xiuze Jiang, Jingang Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Harbin Univ Sci & Technol Sch Mech & Power Engn Harbin 150080 Peoples R China

Robot-assisted thumb rehabilitation can improve the hand function of stroke patients because the thumb accounts for 40% of hand function. However, existing thumb rehabilitation robots are limited in terms of portability, comfort, adaptability, and independent joint actuation. This article proposes an untethered adaptive thumb exoskeleton that actively assists the 3-degree-of-freedom movements of the thumb. The exoskeleton is composed of an adaptive thumb mechanism and a spherical mechanism. The kinematics, statics, and performances of the adaptive thumb mechanism and the spherical mechanism are analyzed. Experimental validation is performed to test the workspace, self-alignment, interaction forces, admittance controller, and grasping assistance performance of the exoskeleton. The workspace and self-aligning experiments prove that the proposed exoskeleton can achieve a large workspace of the thumb joints and realize self-alignment. The interaction force experimental results show that the exoskeleton can reduce the tangential interaction forces by 76.8% and improve comfort. Finally, the control and delicate grasping assistance experiments validate the exoskeleton's ability to realize the delicate grasping of the thumb. These characteristics show that the thumb exoskeleton has the potential to assist delicate thumb rehabilitation.

关键词： Adaptive mechanism interaction force rehabi litation thumb exoskeleton

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Design and Locomotion control of a Dactylopteridae-Inspired Biomimetic Underwater Vehicle With Hybrid Propulsion

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2022年第3期19卷 2054-2066页

作者： Zhang, Tiandong Wang, Rui Wang, Yu Cheng, Long Wang, Shuo Tan, Min Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Ctr Excellence Brain Sci & Intelligence Technol Shanghai 200031 Peoples R China

This article presents the design and implementation of an innovative biomimetic underwater vehicle (BUV) and its locomotion controller. Through mimicking a dactylopteridae, the hybrid propulsion BUV is designed with two symmetrical bio-inspired long-fins and a double-joint fishtail. The mechatronic design of the dactylopteridae-inspired BUV with the pectoral long-fins and a double-joint fishtail is first provided. The two flexible long-fins compose the median and/or paired fin (MPF) propulsion, while the fishtail acts as the body and/or caudal fin (BCF) propulsion. Through the coordination of BCF and MPF propulsion modes, the BUV obtains excellent low-speed locomotion stability and also keeps high maneuverability. Moreover, the locomotion control methods based on central pattern generators (CPGs) model and fuzzy adaptive proportion integral differential (PID) are proposed for this BUV. In the end, the experimental results of the multimode motion and closed-loop motion control demonstrate the feasibility and effectiveness of the mechanism and the locomotion control system.

关键词： Propulsion DC motors Robots control systems Servomotors Underwater vehicles Sports Biomimetic underwater vehicle (BUV) body and or caudal fin (BCF) median and or paired fin (MPF) hybrid propulsion central pattern generators (CPGs) fuzzy proportion integral differential (PID)

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Quantization control for flexible manipulators with PDE model

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ASIAN JOURNAL OF control 2022年第6期24卷 3117-3132页

作者： Wang, Jiacheng Yang, Hongjun Liu, Jinkun Wang, Shuquan Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing Peoples R China Chinese Acad Sci Div Space Explorat Technol & Engn Ctr Space Utilizat Beijing Peoples R China

In this paper, two different quantization control laws are proposed for the single-link manipulator system with horizontal motion and input signal quantization. Considering the characteristics of distributed parameters of the flexible system, the dynamic model of the system is represented by partial differential equations (PDEs) and boundary conditions. One of the control laws is proposed to follow the desired time-varying joint angle and eliminate boundary deformation of the link simultaneously. The other control law is proposed to track the required constant angle and suppress the distributed deformation of the link. The two control schemes can not only guarantee the stability of the system but also meet the control requirements under the premise of input signal quantization. Numerical simulations are provided to verify the performance of the controller.

关键词： boundary control distributed control flexible manipulator system PDE model quantization control

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Meta-Residual Policy Learning: Zero-Trial Robot Skill Adaptation via Knowledge Fusion

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IEEE ROBOTICS AND AUTOMATION LETTERS 2022年第2期7卷 3656-3663页

作者： Hao, Peng Lu, Tao Cui, Shaowei Wei, Junhang Cai, Yinghao Wang, Shuo Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Ctr Excellence Brain Sci & Intelligence Technol Shanghai 200031 Peoples R China

Adapting the mastered manipulation skill to novel objects is still challenging for robots. Recent works have attempted to endow the robot with the ability to adapt to unseen tasks by leveraging meta-learning. However, these methods are data-hungry in the training phase, which limits their application in the real world. In this paper, we propose Meta-Residual Policy Learning (MRPL) to reduce the cost of policy learning and adaptation. During meta-training, MRPL accelerates the learning process by focusing on the residual task-shared knowledge that is hard to be embedded in the hand-engineered controller. During testing, MRPL achieves fast adaptation on similar unseen tasks through fusing task-specific knowledge in the demonstration with task-shared knowledge in the learned policy. We conduct a series of simulated and real-world peg-in-hole tasks to evaluate the proposed method. The experimental results demonstrate that MRPL outperforms prior methods in robot skill adaptation. Code for this work is available at https://***/Bartopt/code4MRPL.

关键词： Task analysis Robots Training Adaptation models Service robots Robot control Costs Machine learning for robot control learning from experience assembly

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A Paradigm Shift for Modeling and Operation of Oil and Gas: From Industry 4.0 in CPS to Industry 5.0 in CPSS

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2024年第7期20卷 9186-9193页

作者： Wang, Xingxia Wang, Yutong Yang, Jing Wang, Xiao Meng, Zonglin Liu, Zhaohai Wang, Fei-Yue Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence S Beijing 100190 Peoples R China Anhui Univ Sch Artificial Intelligence Hefei 266114 Peoples R China Qingdao Acad Intelligent Ind Qingdao 230031 Peoples R China Univ Calif Los Angeles Dept Civil & Environm Engn Los Angeles CA 90024 USA Tangshan Jidong Petr Machinery Co Ltd Tangshan 063299 Hebei Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Under the impetus of Industry 4.0, oil and gas is undergoing an unprecedented digital transformation, and many innovative ideas are proposed. However, the achieved higher efficiency comes at the expense of reduced social consideration, which necessitates more society-related research and calls for a technological paradigm shift. To meet this challenge, this article introduces parallel oil and gas within the framework of parallel intelligence-based Industry 5.0, providing a pivotal transition from cyber-physical systems (CPS) to cyber-physical-social systems (CPSS). A comprehensive review of oil and gas industrial chain that covers upstream, midstream, and downstream is first outlined. Grounded in Industry 5.0, the main principles of parallel oil and gas are then provided, where three kinds of workers (biological workers, digital workers, and robotic workers) and three operation modes (autonomous modes, parallel modes, and expert/emergency modes) collaborate to develop more human-oriented and resilient systems. To realize the desired vision, some enabling technologies, including blockchain, smart contracts, and industrial foundation models, are thereafter listed. Furthermore, computational experiments on fault diagnosis of sucker rod pumps are conducted to illustrate the feasibility and effectiveness of our proposed mechanism. Finally, the future trend toward imaginative intelligence is envisaged.

关键词： Oils Fifth Industrial Revolution Production Fourth Industrial Revolution Biology Service robots Transportation Cyber-physical systems (CPS) cyber-physical-social systems (CPSS) Industry 4.0 Industry 5.0 parallel intelligence parallel oil and gas

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A Preliminary Study on the Functional Coupling between Nerve and Blood Microcirculation for Applications in Rehabilitation Robots

A Preliminary Study on the Functional Coupling between Nerve...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Li, Qingge Dong, Yuanzhe Zhang, Yuxiang Wang, Xin Jiang, Naifu Huang, Jianping Cui, Han Tian, Lan Zheng, Yue Li, Xiangxin Wang, Lin Li, Guanglin Liang, Wenyuan Peng, Liang Fang, Peng Shenzhen Institute of Advanced Technology Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China National Research Center for Rehabilitation Technical Aids Beijing100176 China Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China

ISBN: (纸本)9798350325706

Rehabilitation robots play an important role in the motor function rehabilitation for stroke survivors with hemiplegia. However, the rehabilitation effect of current robots is still limited partly because a single training of motor function can be strongly affected by the decreased blood supply function of the bedridden patients. This work proposed an approach to study the coupling relationship between the motor and blood supply functions by combining the synchronously recorded EEG and cerebral blood oxygen information, where the cerebrations in different movement paradigms were analyzed from an aspect of "functional coupling". The results show that the information of oxyhemoglobin concentration change (ΔHbO) can effectively indicate the cortex activation, and a stronger blood supply is needed in cortexes to perform body movements. The correlations within motor cortexes are significantly stronger than the ones between motor and prefrontal cortexes, and a higher resistance level of extremity training will cause stronger correlations. Calculation of transfer entropy (TE) shows that there exists a bidirectional information transmission between the electrophysiological and blood supply signals, and more information is transmitted always in the direction from ΔHbO to EEG than in the opposite direction. The information transmission or the coupling relationship can be significantly enhanced by extremity movements, and large TE values are achieved in the Theta, Beta and Gamma frequency bands of EEG that correspond to motor functions. This work has demonstrated the functional coupling between nerve and blood microcirculation, which would provide a technical guidance to improve the rehabilitation effect for current robot systems and have great application potentials. © 2023 IEEE.

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