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MRI-guided robot intervention—current state-of-the-art and new challenges

Med-X 2023年第1期1卷 141-181页

作者： Shaoping Huang Chuqian Lou Ying Zhou Zhao He Xuejun Jin Yuan Feng Anzhu Gao Guang-Zhong Yang Institute of Medical Robotics and School of Biomedical Engineering Shanghai Jiao Tong UniversityShanghai 200240China National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy(NERC-AMRT) Shanghai Jiao Tong UniversityShanghai 200240China Materials and Technology Center of Robotics EmpaDübendorf 8600Switzerland State Key Lab of Metal Matrix Composites and School of Materials Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China Institute of Medical Robotics and Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China The Key Laboratory of System Control and Information Processing Ministry of EducationShanghai 200240China

Magnetic Resonance Imaging(MRI)is now a widely used modality for providing multimodal,high-quality soft tissue contrast images with good spatiotemporal resolution but without subjecting patients to ionizing *** addition to its diagnostic potential,its future theranostic value lies in its ability to provide MRI-guided robot intervention with combined structural and functional mapping,as well as integrated instrument localization,target recognition,and in situ,in vivo monitoring of the therapeutic *** of current applications include neurosurgery,breast biopsy,cardiovascular intervention,prostate biopsy and *** applications in targeted drug delivery and MRI-guided chemoembolization are also being *** promising progress has been made in recent years,there are still significant basic science research and engineering *** paper provides a comprehensive review of the current state-of-the-art in MRI-guided robot intervention and allied technologies in actuation,sensing,new materials,interventional instruments,and interactive/real-time *** future research directions and new clinical developments are also discussed.

关键词： MRI-guided robot intervention Actuation Sensing Materials Interventional instruments Interactive/realtime MRI

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Coordinated operation of electricity and hydrogen blended gas networks via correlation-enhanced joint chance-constrained approach

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International Journal of Hydrogen Energy 2025年 149卷

作者： Sicheng Liu Bo Yang Lun Yang Xu Yang Xin Li Zhaojian Wang Kai Ma Xinping Guan State Key Laboratory of Submarine Geoscience School of Automation and Intelligent Sensing Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory for System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China School of Automation Science and Engineering Xi’an Jiaotong University Xi’an 710049 China Key Lab of Industrial Computer Control Engineering of Hebei Province and the School of Electrical Engineering Yanshan University Qinhuangdao 066000 China

Blending green hydrogen into natural gas can effectively promote hydrogen consumption and operational flexibility of electricity-gas coupled networks. However, the volatility of renewable energy sources threatens the operation of green hydrogen production and blending, while existing system-level risk management methods either exhibit over-conservatism or are computationally inefficient when constraints are numerous. Therefore, this paper proposes a correlation-enhanced distributionally robust joint chance-constrained (DRJCC) method for the joint scheduling of electricity and hydrogen-enriched compressed natural gas (E-HCNG) networks, aiming to minimize operating cost while limiting joint violation risk under renewable energy uncertainty. Specifically, before DRJCC, an improved hydrogen fraction model is developed for hydrogen blending, refining the representation of fraction variations by incorporating the buffer effect of line packs. Then, for DRJCC solving, the commonly used Bonferroni approximations are overly conservative in allocating joint violation risks to individual chance constraints, especially when constraints are numerous. To mitigate this, by leveraging strongly violation correlations of operational constraints under affine policies, a grouping-based risk allocation strategy is proposed to reduce the over-conservatism. Theoretical derivations confirm the guarantee of joint violation risk via the proposed method. Additionally, customized transformations are developed to address the non-convexities introduced by variable hydrogen fractions. Case studies demonstrate the effectiveness and superiority of the proposed method.

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Motion Projection Consistency Based 3D Human Pose Estimation with Virtual Bones from Monocular Videos

arXiv

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arXiv 2021年

作者： Wang, Guangming Zeng, Honghao Wang, Ziliang Liu, Zhe Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FD United Kingdom

Real-time 3D human pose estimation is crucial for human-computer interaction. It is cheap and practical to estimate 3D human pose only from monocular video. However, recent bone splicing based 3D human pose estimation method brings about the problem of cumulative error. In this paper, the concept of virtual bones is proposed to solve such a challenge. The virtual bones are imaginary bones between non-adjacent joints. They do not exist in reality, but they bring new loop constraints for the estimation of 3D human joints. The proposed network in this paper predicts real bones and virtual bones, simultaneously. The final length of real bones is constrained and learned by the loop constructed by the predicted real bones and virtual bones. Besides, the motion constraints of joints in consecutive frames are considered. The consistency between the 2D projected position displacement predicted by the network and the captured real 2D displacement by the camera is proposed as a new projection consistency loss for the learning of 3D human pose. The experiments on the Human3.6M dataset demonstrate the good performance of the proposed method. Ablation studies demonstrate the effectiveness of the proposed inter-frame projection consistency constraints and intra-frame loop constraints. Copyright © 2021, The Authors. All rights reserved.

关键词： E-learning

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Distributed urban freeway traffic optimization considering congestion propagation

arXiv

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arXiv 2021年

作者： Gao, Fengkun Yang, Bo Chen, Cailian Guan, Xinping Zhang, Yang Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China Shanghai Municipal Urban-Rural Construction and Transportation Development Institute China

Traffic optimization strategies are imperative for improving the performance of transportation networks. Most traffic optimization strategies only depend on traffic states of congested road segments, where congestion propagation is neglected. Therefore, we propose a distributed traffic optimization strategy for urban freeways considering the potential congested road segments caused by congestion propagation, called potential-homogeneous-area (PHA). Utilizing the historical traffic density data, we firstly quantify the effect of congestion propagation and identify PHA by applying the proposed spatio-temporal lambda-connectedness method. Meanwhile, dynamic capacity constraints of PHA are determined and are integrated with cell transmission model (CTM) in a centralized traffic optimization problem. To reduce computational complexity and improve scalability, we then propose a doubleconsensus- based alternating direction method of multipliers algorithm (DC-ADMM) to handle the neighbor coupling constraints and global coupling constraints for solving the problem in a fully distributed way. We prove that the proposed DC-ADMM algorithm converges to the optimal solution in the condition of convex objective function. Finally, simulations based on real traffic density data, collected in Inner Ring Road, Shanghai, China, reveal the effectiveness of our proposed strategy. © 2021, CC BY.

关键词： Roads and streets

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Federated Multi-Agent Deep Reinforcement Learning Approach via Physics-Informed Reward for Multi-Microgrid Energy Management

arXiv

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arXiv 2022年

作者： Li, Yuanzheng He, Shangyang Li, Yang Shi, Yang Zeng, Zhigang School of Artificial Intelligence and Automation Key Laboratory on Image Information Processing and Intelligent Control of Ministry of Education Huazhong University of Science and Technology Wuhan430074 China China-Belt and Road Joint Laboratory on Measurement and Control Technology Wuhan430074 China China-EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Wuhan430074 China School of Electrical Engineering Northeast Electric Power University Jilin132012 China The Department of Mechanical Engineering University of Victoria VictoriaBC V8P 5C2 Canada

The utilization of large-scale distributed renewable energy promotes the development of the multi-microgrid (MMG), which raises the need of developing an effective energy management method to minimize economic costs and keep self energy-sufficiency. The multi-agent deep reinforcement learning (MADRL) has been widely used for the energy management problem because of its real-time scheduling ability. However, its training requires massive energy operation data of microgrids (MGs), while gathering these data from different MGs would threaten their privacy and data security. Therefore, this paper tackles this practical yet challenging issue by proposing a federated multi-agent deep reinforcement learning (F-MADRL) algorithm via the physics-informed reward. In this algorithm, the federated learning (FL) mechanism is introduced to train the F-MADRL algorithm thus ensures the privacy and the security of data. In addition, a decentralized MMG model is built, and the energy of each participated MG is managed by an agent, which aims to minimize economic costs and keep self energy-sufficiency according to the physics-informed reward. At first, MGs individually execute the self-training based on local energy operation data to train their local agent models. Then, these local models are periodically uploaded to a server and their parameters are aggregated to build a global agent, which will be broadcasted to MGs and replace their local agents. In this way, the experience of each MG agent can be shared and the energy operation data is not explicitly transmitted, thus protecting the privacy and ensuring data security. Finally, experiments are conducted on Oak Ridge national laboratory distributed energy control communication lab microgrid (ORNL-MG) test system, and the comparisons are carried out to verify the effectiveness of introducing the FL mechanism and the outperformance of our proposed F-MADRL. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

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Spatial non-locality induced non-markovian EIT in a single giant atom

arXiv

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arXiv 2021年

作者： Zhu, Y.T. Wu, R.B. Xue, S. Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Department of Automation Tsinghua University Beijing100084 China Beijing National Research Center for Information Science and Technology Beijing100084 China

In recent experiments, electromagnetically induced transparency (EIT) were observed with giant atoms, but nothing unconventional were found from the transmission spectra. In this letter, we show that unconventional EIT does exist in giant atoms, and indicate why it has not been observed so far. Different from these existing works, this letter presents a consistent theory including a real space method and a time delayed master equation for observing unconventional EIT. We discover that this phenomenon is a quantum effect which cannot be correctly described in a semi-classical way as those in recent works. Our theory shows that it can be observed when the time delay between two neighboring coupling points is comparable to the relaxation time of the atom, which is crucial for a future experimental observation. This new phenomenon results from inherent non-locality of the giant atom, which physically forces propagating fields to be standing waves in space and the atom exhibiting retardations in time. Our theory establishes a framework for application of nonlocal systems to quantum information processing. Copyright © 2021, The Authors. All rights reserved.

关键词： Atoms

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Deep Rank-Consistent Pyramid Model for Enhanced Crowd Counting

arXiv

引用

arXiv 2022年

作者： Gao, Jiaqi Huang, Zhizhong Lei, Yiming Shan, Hongming Wang, James Z. Wang, Fei-Yue Zhang, Junping The Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China The Institute of Science and Technology for Brain-inspired Intelligence MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China The Shanghai Center for Brain Science and Brain-Inspired Technology Shanghai201210 China The College of Information Sciences and Technology The Pennsylvania State University University ParkPA16802 United States The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The Institute of Systems Engineering Macau University of Science and Technology China Qingdao Academy of Intelligent Industries Qingdao266109 China

Most conventional crowd counting methods utilize a fully-supervised learning framework to establish a mapping between scene images and crowd density maps. They usually rely on a large quantity of costly and time-intensive pixel-level annotations for training supervision. One way to mitigate the intensive labeling effort and improve counting accuracy is to leverage large amounts of unlabeled images. This is attributed to the inherent self-structural information and rank consistency within a single image, offering additional qualitative relation supervision during training. Contrary to earlier methods that utilized the rank relations at the original image level, we explore such rank-consistency relation within the latent feature spaces. This approach enables the incorporation of numerous pyramid partial orders, strengthening the model representation capability. A notable advantage is that it can also increase the utilization ratio of unlabeled samples. Specifically, we propose a Deep Rank-consistEnt pyrAmid Model (DREAM), which makes full use of rank consistency across coarse-to-fine pyramid features in latent spaces for enhanced crowd counting with massive unlabeled images. In addition, we have collected a new unlabeled crowd counting dataset, FUDAN-UCC, comprising 4,000 images for training purposes. Extensive experiments on four benchmark datasets, namely UCF-QNRF, ShanghaiTech PartA and PartB, and UCF-CC-50, show the effectiveness of our method compared with previous semi-supervised methods. The codes are available at https://***/bridgeqiqi/DREAM. Copyright © 2022, The Authors. All rights reserved.

关键词： Image enhancement

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Observer-like Model Reference Adaptive Augmenting based fixed-wing UAV control

Observer-like Model Reference Adaptive Augmenting based fixe...

引用

第三十九届中国控制会议

作者： Jizhang Xiong Ye Yang Zhongtao Cheng Lei Liu Yongji Wang Huijin Fan National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and AutomationHuazhong University of Science and Technology Science and Technology on Aerospace Intelligent Control Laboratory Beijing Aerospace Automatic Control Institute

This paper proposed an observer-like model reference adaptive augmenting control(OMRAAC) design method for a class of multi-input multi-output systems with uncertainty, which can improve the dynamic performance of the system. This control system design method can perform adaptive augmenting control design without changing the original baseline controller of the system(such as PID control, LQR control, etc.), to cope with possible uncertainty in the system and improve the tracking performance of the system. At the same time, in order to suppress the transient oscillation of the system caused by the large adaptive rates, the state tracking error is introduced into the reference model, and an observer-like reference model is designed to improve the dynamic process of the system. Finally, in order to verify the effectiveness of the method, simulation and analysis are performed on the longitudinal short-period model of the fixed-wing UAV, to verify the effectiveness of the method. The simulation compares the tracking performance of the control system based on the LQR controller, the traditional Model Reference Adaptive augmented Augmented controller, and the proposed OMRAAC method. The simulation results show that the observer-like adaptive augmenting control can effectively suppress the system uncertainties, and improve the dynamic response performance of the system.

关键词： adaptive augmenting control fixed-wing UAV control oscillation suppression

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Research on Attitude control of Quadrotor UAV Based on Active Disturbance Rejection control

Research on Attitude Control of Quadrotor UAV Based on Activ...

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第32届中国控制与决策会议

作者： Zuling Song Yongji Wang Lei Liu Zhongtao Cheng Ye Yang National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and AutomationHuazhong University of Science and Technology Science and Technology on Aerospace Intelligent Control Laboratory Beijing Aerospace Automatic Control Institute

Aiming at enhancing the disturbance suppression ability of attitude control of quadrotor UAV（Unmanned Aerial Vehicle）,design an ADRC（Active Disturbance Rejection control） based on quadrotor *** from the traditional trial adjustment of the parameter b0 in ADRC design,it can be derived according to the characteristics of the quadrotor model in this ***,a non-linear kinematic model of a quadrotor UAV is established,and then each module of the ADRC is designed and debugged by ***,the system is simulated and *** experimental results show that ADRC has a stronger disturbance suppression capability than PID control,which greatly improves the stability of the system and enhances the drone’s flight control ability in complex environments.

关键词： Quadrotor UAV ADRC Attitude control Disturbance observation Disturbance Rejection

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Simultaneous Precision Assembly of Multiple Objects through Coordinated Micro-robot Manipulation

Simultaneous Precision Assembly of Multiple Objects through ...

引用

IEEE International Conference on Robotics and automation (ICRA)

作者： Song Liu Yuyu Jia You-Fu Li Yao Guo Haojian Lu ShanghaiTech Automation and Robotics Center School of Information Science and Technology ShanghaiTech University Shanghai China City University of Hong Kong Kowloon Hong Kong Institute of Medical Robotics Shanghai Jiaotong University Shanghai China State Key Laboratory of Industrial Control and Technology and Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

Simultaneous assembly of multiple objects is a key technology to form solid connections among objects to get compact structures in precision assembly and micro-assembly. Dramatically different from traditional assembly of two objects, the interaction among multiple objects is more complicated on analysis and control. During simultaneous assembly of multiple objects, there are multiple mutually effected contact surfaces, and multiple force sensors are needed to perceive the interaction status. In this paper, a coordinated micro-robot manipulation strategy is proposed for simultaneous assembly problem, which is based on microscopic vision and force information. Taking simultaneous assembly of three objects as an instance, the proposed method is well articulated, including calibration of assembly system, force analysis for each contacting surface, and insertion control strategy for assembly process. The proposed method is applicable also to case with more objects. Experiment results demonstrate effectiveness of the proposed method.

关键词： automation Shape Microscopy Conferences Force Process control Robot sensing systems

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