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A Safety-Enhanced Multi-Modal Objectives Motion Fusion Method for Autonomous Retraction in Robotic Surgery

IEEE Transactions on Automation Science and Engineering 2025年 22卷 15990-16000页

作者： Shi, Yudong Mo, Hangjie Xiao, Xilin Fang, Jin Li, Ling Min, Kang Li, Xiaojian Hefei University of Technology School of Management Hefei China Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making (Ministry of Education) Hefei China

In minimally invasive surgery (MIS), tissue retraction is critical for exposing the surgical site and facilitating pathological tissue excision. However, tissue retraction in MIS is subject to multiple constraints, including restricted field of view, non-damaging tissue retraction force, and limited instrument operating range, which hinder the safe and continuous retraction of tissue during robotic-assisted surgery. This paper introduces a novel autonomous retraction method for MIS, capable of safely retracting tissue within the aforementioned multiple constraints, assisting the surgeon in tissue excision. The method takes into account information from three different modalities: vision, force, and position. Based on these, three distinct control objectives are defined: retraction angle, retraction force, and safety space constraints, with an individual controller and modelpredictive evaluation function designed for each objective. We propose a novel multi-objective motion fusion strategy designed to balance three distinct control objectives. This strategy evaluates the sensitivity of each objective to changes in the system state by comparing the gradients of their respective prediction evaluation functions and fuses the control inputs of the individual controllers. The proposed method allows for rapid addition or removal of objectives without altering the algorithmic framework. Experiments with phantoms and ex vivo animal tissue are conducted on robotic platform to validate the effectiveness of the proposed method in various configurations. © 2004-2012 IEEE.

关键词： motion fusion robot autonomy surgical robot tissue retraction

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Energy storage resources management:Planning,operation,and business model

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Frontiers of Engineering Management 2022年第3期9卷 373-391页

作者： Kaile ZHOU Zenghui ZHANG Lu LIU Shanlin YANG School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education Hefei University of TechnologyHefei 230009China

With the acceleration of supply-side renewable energy penetration rate and the increasingly diversified and complex demand-side loads,how to maintain the stable,reliable,and efficient operation of the power system has become a challenging issue requiring *** of the feasible solutions is deploying the energy storage system(ESS)to integrate with the energy system to stabilize ***,considering the costs and the input/output characteristics of ESS,both theinitial configuration process and the actual operation process require efficient *** study presents a comprehensive reviewof managing ESs from the perspectives of planning,operation,and business *** of all,in terms of planning and configuration,it is investigated from capacity planning,location planning,as well as capacity and location combined *** process is generally the first step in deploying ***,it explores operation management of ESS from the perspectives of state assessment and operation *** so-called state assessment refers to the assessment of three aspects:The state of charge(SOC),the state of health(SOH),and the remaining useful life(RUL).The operation optimization includes ESS operation strategy optimization and joint operation ***,it discusses the business models of *** business models involve ancillary services and load transfer,while emerging business models include electric vehicle(EV)as energy storage and shared energy storage.

关键词： energy storage system energy storage resources management planning configuration operational management business model

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Industrial False Signal Recognition Based on Deep Learning with Focal Loss

Industrial False Signal Recognition Based on Deep Learning w...

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作者： Xu, Qifa Cheng, Qiliang Jiang, Cuixia Wang, Xiangxiang School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei230009 China

False signals often occur in actual industrial environments. They are however treated as abnormal ones, which will lead to unexpected equipment downtime and production loses. Consider the memory limitations of edge computing, how to recognize them accurately with lightweight models is an important but difficult work. To this end, we develop a novel scheme based on deep learning with focal loss. This scheme first converts original one-dimensional waveform signals into time-frequency graphs through continuous wavelet transform. These graphs are then fed into a convolutional neural network (CNN) for binary classification. Finally, focal loss function is introduced into the CNN model to solve the problem of different types of misclassification costs in recognizing false signals. We verify the effectiveness of this scheme on a real-world application. The results show that our scheme is a high-quality classifier with an accuracy of 98.42%, a Precision of 98.68%, a Recall of 98.18%, and a specificity of 98.68%, which is efficient in recognizing false signals and performs better than several competing models. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolutional neural networks

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Safety assessment of marine high-end equipment based on evidential reasoning approach under fuzzy uncertainty

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Journal of intelligent and Fuzzy Systems 2024年第4期46卷 7495-7520页

作者： Zhou, Mi Xiong, Xue-Di Pei, Feng School of Management Hefei University of Technology Anhui Hefei China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Anhui Hefei China

Marine high-end equipment reflects a country's comprehensive national strength. The safety assessment of it is very important to avoid accident either from human or facility factors. Attribute structure and assessment approach are two key points in the safety assessment of marine high-end equipment. In this paper, we construct a hierarchical attribute structure based on literature review and text mining of reports and news. The hierarchical attribute structure includes human, equipment, environment and management level. The correlations among these attributes are analyzed. The assessment standards of attributes are described in details. Different evaluation grades associated with attributes are transformed to a unified one by the given rules. As for the assessment approach, the evidential reasoning approach is applied for uncertain information fusion. Group analytical hierarchical process is used to generate attribute weights from a group of experts, where process aggregation method and result aggregation method are combined in a comprehensive way. The importance of expert is computed by the uncertainty measure of expert's subjective judgment. A drilling platform is finally assessed by the proposed attribute structure and assessment approach to illustrate the effectiveness of the assessment framework. © 2024 - IOS Press. All rights reserved.

关键词： Safety engineering

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Generative method for aerodynamic optimization based on classifier-free guided denoising diffusion probabilistic model

arXiv

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arXiv 2025年

作者： Deng, Shisong Zhang, Qiang Cai, Zhengyang School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei China

Recently, inverse design approach, which directly generates optimal aerodynamic shape with neural network models to meet designated performance targets, has drawn enormous attention. However, the current state-of-the-art inverse design approach for airfoils, which is based on generative adversarial network, demonstrates insufficient precision in its generating and training processes and struggles to reveal the coupling relationship among specified performance indicators. To address these issues, the airfoil inverse design framework based on the classifier-free guided denoising diffusion probabilistic model (CDDPM) is proposed innovatively in this paper. First, the CDDPM can effectively capture the correlations among specific performance indicators and, by adjusting the classifier-free guide coefficient, generate corresponding upper and lower surface pressure coefficient distributions based on designated pressure features. These distributions are then accurately translated into airfoil geometries through a mapping model. Experimental results using classical transonic airfoils as examples show that the inverse design based on CDDPM can generate a variety of pressure coefficient distributions, which enriches the diversity of design results. Compared with current state-of-the-art Wasserstein generative adversarial network methods, CDDPM achieves a 33.6% precision improvement in airfoil generating tasks. Moreover, a practical method to readjust each performance indicator value is proposed based on global optimization algorithm in conjunction with active learning strategy, aiming to provide rational value combination of performance indicators (i.e. meeting aerodynamic constraints) for the inverse design framework. This work is not only suitable for the airfoils design, but also has the capability to apply to optimization process of general product parts targeting selected performance indicators. Copyright © 2025, The Authors. All rights reserved.

关键词： Generative adversarial networks

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A data-driven soft-sensing model of matte grade in oxygen-rich side blow bath smelting process

A data-driven soft-sensing model of matte grade in oxygen-ri...

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Chinese Control and Decision Conference, CCDC

作者： Gang Yu Mao-Qi He National Key Laboratory of Intelligent Optimization Manufacturing for Mining and Metallurgy Process Beijing General Research Institute of Mining and Metallurgy Beijing China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

A data-driven soft sensing technique is proposed to predict the matte grade, which is aimed at the problem of delay in traditional methods for sampling and determining the matte grade in oxygen-rich side blow bath smelting (OSBS), resulting in the inability to control and optimize the process in real time. This method is based on real-time detected process data and utilizes particle swarm optimization (PSO) algorithm to optimize dynamic process features to construct the optimal input feature set. For the datasets after feature selection, a kernel based extreme learning machine (KELM) is used for regression model training. To adapt to the instant variations and dynamics of the copper smelting process, a local learning strategy combining sliding windows is introduced, which in turn builds an instant learning kernel extreme learning machine regressor. This instant learning regressor is particularly suitable for online learning and real-time prediction due to the simplicity, efficiency, and low time consumption of the KELM algorithm. The feasibility and effectiveness of the proposed method are verified through experiments conducted with data collected on an actual smelting production line.

关键词： Training Adaptation models Heuristic algorithms Smelting process control Feature extraction Real-time systems

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Two-stage charge and discharge optimization of battery energy storage systems in microgrids considering battery state of health

Two-stage charge and discharge optimization of battery energ...

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IEEE International Conference on Power and Power and Renewable Energy (ICPRE)

作者： Zenghui Zhang Kaile Zhou Shanlin Yang Key Laboratory of Process Optimization and Intelligent Decision-Making School of Management Hefei University of Technology Hefei China

An important figure-of-merit for battery energy storage systems (BESSs) is their battery life, which is measured by the state of health (SOH). In this study, we propose a two-stage model to optimize the charging and discharging process of BESS in an industrial park microgrid (IPM). The first stage is used to optimize the charging and discharging time and the corresponding amount of the charging and discharging energy from the BESS, in which the SOH is considered. Subsequently, all battery packs need to be coordinated to ensure a reasonable BESS operation. In order to prolong the service life of the BESS, the second stage of the model allocates the charging and discharging of all battery packs on the basis of the first stage scheduling results. The proposed loss-calculation method is used to calculate the battery pack loss and then to calculate the SOHs of battery packs. It can be seen from the simulation results that the scheduling results considering the SOH are more realistic. Furthermore, the proposed charging and discharging allocation strategy can effectively coordinate the SOH change of all battery packs without causing a significant increase in the battery pack loss of the battery packs.

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Robust PD-type iterative learning control design for uncertain batch processes subject to nonrepetitive disturbances 41

Robust PD-type iterative learning control design for uncerta...

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第41届中国控制会议

作者： Robert Maniarski Wojciech Paszke Shoulin Hao Hongfeng Tao Institute of Automation Electronic and Electrical EngineeringUniversity of Zielona Góra Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper develops PD-type iterative learning control schemes for a class of uncertain batch processes subject to nonrepetitive *** means of two-dimensional/repetitive setting,the sufficient conditions for batch-to-batch error convergence and H disturbance attenuation are formulated and ***,the procedure for computing the desired control law matrices is formulated in terms of solvability of linear matrix *** proposed control law is able to fulfil the imposed design specifications,i.e.,they are suitable for the batch processes with time-varying uncertainties as well as non-repetitive *** illustrative example is used to validate the proposed control scheme and demonstrates a possible applicability of the developed results.

关键词： iterative learning control repetitive processes batch processes robust control nonrepetitive disturbances

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An Integrated Position-velocity-force Method for Safety-enhanced Shared Control in Robot-assisted Surgical Cutting

An Integrated Position-velocity-force Method for Safety-enha...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Xilin Xiao Xiaojian Li Yudong Shi Jin Fang Lin Li Pengfei He Hangjie Mo School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-Making Hefei University of Technology Hefei China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Numerous studies have emphasized the application of autonomous intelligence in human-robot shared control to enhance surgical convenience and efficiency. However, the neglect of human dominance may reduce surgical safety. This paper developed a safety-enhanced human-robot shared control method by intelligently allocating control authority, with the surgeon remaining the leader during the surgical procedure. Three controllers are designed initially, including a master hand position (MP) controller and a master hand velocity (MV) controller related to the surgeon's manipulation, and a planned trajectory tracking (PT) controller related to the robot. In precision surgical manipulation scenarios, precise tracking of the human's operation is achieved by combining MP and MV controllers, while a combination of MV and PT controllers is developed in high-efficiency surgical scenarios, which relaxes the requirement for precise tracking of hand position and enables precise robot assistance guided by the velocity of human hand. The autonomous scenarios and controllers switching are accomplished through a motion fusion mechanism, which is achieved via optimizing evaluation functions that are reliant on future states. Furthermore, a force feedback mechanism is proposed to help human understand the intent of autonomous control to improve safety. The feasibility and effectiveness of this method have been validated through simulations and experiments.

关键词： Medical robotics Trajectory tracking Force feedback Dynamics Surgery Switches Controllability

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Multi-keyframe Guided Points Tracking Method for Enhanced Robotic Surgery

Multi-Keyframe Guided Points Tracking Method for Enhanced Ro...

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IEEE International Conference on Robotics and Biomimetics

作者： Xiaojian Li Tongtong Li Xiang Ma Ling Li Hangjie Mo Jieyu Zheng School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-Making Hefei University of Technology Hefei China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Points tracking provides target guidance for the basic tasks of robotic surgery, such as autonomous cutting, autonomous suturing, and surgical navigation. Existing invivo tracking algorithms mainly consider region-level tracking, making it difficult to achieve pixel-level accuracy. This paper proposes a multi-keyframe guided tracking method (MKTracking) for robotic surgery, which achieves long-term dynamic tracking of any point on endoscopic images. An incremental keyframe pool building block based on time interval and image appearance is proposed, which contains keyframe basic information, tracking patch and tracking points. Besides, an online multi-keyframe query mechanism is designed to efficiently retrieves the three most similar templates from the keyframe pool based on the number of feature matches within the target patch. This mechanism can realize the identification of target moving out and the re-tracking of target reappearance. Points tracking result is obtained by fusing the optical flow results within the target patch across multiple frames. We evaluated MKTracking using ground-truth data, and the results demonstrated that our approach achieved superior tracking performance.

关键词： Target tracking Accuracy Minimally invasive surgery Navigation Heuristic algorithms Buildings Real-time systems Robots Optical flow Videos

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