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Multicriteria game approach to air-to-air combat tactical decisions for multiple UAVs

Journal of Systems Engineering and Electronics 2023年第6期34卷 1447-1464页

作者： JIANG Ruhao LUO He MA Yingying WANG Guoqiang School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization&Intelligent Decision-making Ministry of EducationHefei 230009China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei 230009China

Air-to-air combat tactical decisions for multiple unmanned aerial vehicles(ACTDMU)are a key decision-making step in beyond visual range *** influencing factors,strong antagonism and real-time requirements need to be considered in the ACTDMU *** this paper,we propose a multicriteria game approach to *** approach consists of a multicriteria game model and a Pareto Nash equilibrium *** this model,we form the strategy profiles for the integration of air-to-air combat tactics and weapon target assignment strategies by considering the correlation between them,and we design the vector payoff functions based on predominance *** propose a algorithm of Pareto Nash equilibrium based on preference relations using threshold constraints(PNE-PRTC),and we prove that the solutions obtained by this algorithm are refinements of Pareto Nash equilibrium *** numerical experiments indicate that PNE-PRTC algorithm is considerably faster than the baseline algorithms and the performance is *** on large-scale instances,the Pareto Nash equilibrium solutions can be calculated by PNEPRTC algorithm at the second *** simulation experiments show that the multicriteria game approach is more effective than one-side decision approaches such as multiple-attribute decision-making and randomly chosen decisions.

关键词： tactical decision multicriteria game preference relation Pareto Nash equilibrium.

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

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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 model-predictive 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. Note to Practitioners—The motivation of this study is to address the challenge of autonomous tissue retraction in robotic-assisted laparoscopic surgery under multiple constraints. Existing methods primarily focus on single objectives and overlook the conflicts and coordination required among multi-modal objectives such as retraction angle, force, and safety space constraints. These limitations reduce the safety of robotic syste

关键词： motion fusion robot autonomy surgical robot Tissue retraction

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Automated Cross-modal Registration Algorithm For Liver Surgery Navigation 24

Automated Cross-modal Registration Algorithm For Liver Surge...

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2nd International Conference on Frontiers of intelligent Manufacturing and Automation, CFIMA 2024

作者： Li, Ling Chen, Yulu Shen, Ziming Mo, Hangjie Li, Xiaojian Hefei University of Technology Anhui Hefei China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Anhui Hefei China

ISBN: (纸本)9798400710681

By overlaying preoperative models and their internal structures onto endoscopic images, cross-modal registration methods restore a surgeon’s ability to perceive three-dimensional information in laparoscopic scenes, providing precise surgical navigation. Many cross-modal registration and surgical navigation techniques are heavily reliant on manually annotated landmark information. An automated preoperative-to-intraoperative cross-modal registration pipeline for 3D-2D registration in laparoscopic liver interventions is proposed in this paper, eliminating manual intervention. Firstly, two convolutional neural networks are trained to autonomously obtain contours as landmarks from preoperative models and intraoperative endoscopic images. Secondly, an improved Random Sample Consensus-based perspective-n-points method with segmentation constraints is proposed to calculate the transformation from the preoperative model to the endoscopic coordinate system using marked points of key anatomical structures. Finally, the preoperative model is projected onto the intraoperative coordinate system to achieve augmented reality visual guidance. In experiments conducted on a public liver registration dataset, the method proposed in this paper achieves comparable results to registration methods based on manual annotations, validating the effectiveness of the proposed pipeline. © 2024 Copyright held by the owner/author(s).

关键词： Augmented reality

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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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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

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

ISBN: (纸本)9781665481090

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. © 2024 IEEE.

关键词： Optical flows

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Two-stage charge and discharge optimization of battery energy storage systems in microgrids considering battery state of health 8

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

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8th International Conference on Power and Renewable Energy, ICPRE 2023

作者： Zhang, Zenghui Zhou, Kaile Yang, Shanlin Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making School of Management Hefei230009 China

ISBN: (纸本)9798350328813

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. © 2023 IEEE.

关键词： Battery energy storage system Charging and discharging optimization Industrial park microgrid State of health

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Extreme Risk Measurement of Carbon Market Considering Multifractal Characteristics

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Journal of Systems Science & Complexity 2023年第6期36卷 2497-2514页

作者： ZHU Dandan ZHANG Chen PAN Di School of Management Hefei University of TechnologyHefei230009China School of Economics and Management Shanghai University of Political Science and LawShanghai201701China Key Laboratory of Process Optimization and Intelligent Decision-Making Hefei University of TechnologyHefei230009China

Influenced by the global economy,politics,energy and other factors,the price of carbon market fluctuates *** is of great practical significance to explore a suitable measurement method of extreme risk of carbon *** that the return series of carbon market has the characteristics of leptokurtosis,fat tail,skewness and multifractal,and there maybe many extreme risk values in the carbon market,this paper introduces the Skewed-t distribution which can describe the characteristics of leptokurtosis,fat tail and skewness of return series into MSM model which can describe multifractal characteristic of return series to model volatility of carbon *** the basis,based on the extreme value theory,this paper constructs Skewed-t-MSM-EVT model to measure extreme risk of carbon *** paper chooses EUA market as the object to study extreme risk of carbon market,and draws the following conclusions:Skewed-t-MSM-EVT model has significantly higher prediction accuracy for carbon market's Va R than MSM-EVT models under other distributions(including normal distribution,t distribution,GED distribution);Skewed-t-MSM-EVT model is superior to traditional Skewed-t-FIGARCH-EVT and Skewed-t-GARCH-EVT models in predicting carbon market's Va *** research has important practical significance for accurately grasping the risk of carbon market and promoting energy conservation and emission reduction.

关键词： Carbon market extreme value theory multifractal Skewed-t distribution VaR

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Joint optimization of Production and Shipping for Small Orders Considering Less-Than-Container Loading 4th

Joint Optimization of Production and Shipping for Small Orde...

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4th International Conference on Resources and Environmental Research, ICRER 2022

作者： Tian, Yajing Wang, Guoqiang Chen, Yingying Luo, He School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization & Intelligent Decision-Making Ministry of Education Hefei China

ISBN: (纸本)9783031318078

This paper introduces a joint optimization problem of production and shipping for overseas small orders considering less-than-container loading (LCL) in manufacturing enterprises. The problem consists of finding a production schedule together with a LCL shipping scheme simultaneously to minimize the total cost. An integer programming model is developed, and the genetic algorithm of enhanced elite reservation (SEGA) is used to solve large-sized instances. Besides, the performance of SEGA is compared with the classical genetic algorithm (SGA) and stallion genetic algorithm (stud GA). It is statistically shown that SEGA outperforms other algorithms in finding near-optimal solutions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Loading

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Agile Earth Observation Satellite Scheduling Algorithm for Emergency Tasks Based on Multiple Strategies

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Journal of Systems Science and Systems Engineering 2021年第5期30卷 626-646页

作者： Haiquan Sun Wei Xia Zhilong Wang Xiaoxuan Hu aSchool of Management Hefei University of TechnologyHefeiChina Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of EducationHefeiChina

During the execution of imaging tasks,satellites are often required to observe natural disasters,local wars,and other emergencies,which regularly interferes with the execution of existing ***,rapid satellite scheduling is urgently *** a new generation of three degree-of-freedom(roll,pitch,and yaw)satellites,agile earth observation satellites(AEOSs)have longer variable-pitch visible time windows for ground targets and are capable of observing at any time within the time ***,they are very suitable for emergency ***,current task scheduling models and algorithms ignore the time,storage and energy consumed by ***,these cannot make full use of the AEOS capabilities to optimize the scheduling for emergency *** this study,we present a fine scheduling model and algorithm to realize the AEOS scheduling for emergency ***,a novel time window division method is proposed to convert a variable-pitch visible time window to multiple fixed-pitch visible time ***,a model that considers flexible pitch and roll capabilities is ***,a scheduling algorithm based on merging insertion,direct insertion,shifting insertion,deleting insertion,and reinsertion strategies is proposed to solve conflicting problems *** verify the effectiveness of the algorithm,48 groups of comparative experiments are carried *** experimental results show that the model and algorithm can improve the emergency task completion efficiency of AEOSs and reduce the disturbance measure of the ***,the proposed method can support hybrid satellite resource scheduling for emergency tasks.

关键词： Agile earth observation satellites emergency tasks merging insertion shifting insertion

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3DGS-based Tracking of Articulated Instruments for Instruments-Tissue Interaction Estimation in Robot-assisted Minimally Invasive Surgery

3DGS-based Tracking of Articulated Instruments for Instrumen...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Li, Xiaojian Shen, Lili Li, Ling Mo, Hangjie Wang, Xin Ma, Xiang Zheng, Jieyu School of Management Hefei University of Technology Hefei China Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making Hefei China West China Hospital Sichuan University Sichuan China

ISBN: (纸本)9781665481090

3D information of surgical scene potentially enhances the accuracy of surgical navigation and facilitate the automation of robot-assisted surgery. However, current research seldom considers the relative 3D position between instruments and tissue. In this paper, the instruments-tissue interaction estimation method is proposed to obtain the relative distance between instruments and tissue. The 3D Gaussian representation of instruments is established preoperatively, making the pose of instruments the only parameter to be learned and updated. Based on this, the instrument pose estimation method is proposed, which applies 3DGS (3D Gaussian Splatting) to the instrument Gaussian model to obtain rendered color images, projection masks, and depth maps. These are aligned with the input images, segmented masks and depth from stereo depth estimation to construct the target loss. By backpropagating through the target loss, the optimal instrument pose is obtained. The L1 loss and smooth loss based on TPS (the Thin Plate Spline) are used to complete the depth of tissue occluded by instruments. The instruments-tissue interaction is estimated by the nearest distance between instrument and tissue. The experimental results indicate an average error of 0.94 mm and an accuracy of 90.40% with an error less than 2mm in estimating relative 3D distance between instruments and tissue. © 2024 IEEE.

关键词： Robotic surgery

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Learning Adaptive Mapless Navigation Skills Through Evidential Deep Learning

Learning Adaptive Mapless Navigation Skills Through Evidenti...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Zhao, Cancan Yan, Yufeng Liu, Xuhao Zhang, Shuai Ouyang, Bo Hefei University of Technology School of Management Hefei China Hefei University of Technology The Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei China

ISBN: (纸本)9798350327182

Traditional navigation methods tend to design and train navigation skills based on the consideration of multi-scenario applicability and perform well in general scenarios. However, this results in sub-optimal navigation performance in some context-specific scenarios, such as navigating through open or crowded scenarios. While some existing navigation skills can achieve satisfactory performance in context-specific scenarios, e.g., using PID in open scenarios and reinforcement learning-based training methods in crowded scenarios. Most methods currently do without consideration of the integration of navigation skills and contextual understanding. To address this gap, we propose an adaptive mapless navigation method to utilize the optimal capabilities of each skill corresponding to the context-specific scenario. Specifically, we package several existing navigation skills and train a scenario classifier to enable the agent to automatically select the most appropriate skill based on the current scenario. Furthermore, we incorporate evidential deep learning (EDL) to assess classification uncertainty and ensure the safe switching of navigation skills. Our method was tested in both simulated and real scenarios, and the results of the experiments confirmed the effectiveness and generalization of our method. Moreover, the proposed method exhibits notably enhanced, context-sensitive efficiency within a hybrid multi-scenario setting, in comparison to a single navigation skill. © 2023 IEEE.

关键词： Navigation

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