Journal of Field Robotics最新文献

{"title":"Design and Optimization of Controller-Based Approach for Magnetic-Field Driven Robotic Arm Joints and End-Effector","authors":"Manpreet Kaur,&nbsp;Swati Sondhi,&nbsp;Venkata Karteek Yanumula","doi":"10.1002/rob.22564","DOIUrl":"https://doi.org/10.1002/rob.22564","url":null,"abstract":"<div>\u0000 \u0000 <p>Magnetic Levitation (Maglev) is a technique that involves suspending an object using a magnetic field. This study presents a novel approach for robotic arm joints and end effectors by utilizing the functioning prototype of the Maglev system due to their similar functionality. The proposed approach utilizes a fractional-order enhanced model reference adaptive controller (FOEMRAC) in conjunction with the Coyote optimization algorithm (COA) to control the stability of levitating magnetic objects. The FOEMRAC system employs a modified MIT rule as its adaptation mechanism. The simulation is performed using the Quanser Maglev system, and a comparison is done with other state-of-the-art techniques such as linear quadratic regulator (LQR), particle swarm optimization-LQR (PSO-LQR), LQR + proportional integral (LQR + PI), LQR + proportional integral derivative (LQR + PID), proportional integral voltage + PI (PIV + PI), enhanced model reference adaptive controller (EMRAC), FOEMRAC, and PSO-FOEMRAC, respectively. The robustness of the controllers is assessed using various integral error criteria, such as integral absolute error (IAE), integral square error (ISE), and integral time absolute error (ITAE), respectively. Additionally, rise time, settling time, overshoot, and undershoot have been employed for comparison purposes with load disturbance and parametric uncertainties. The results are also validated on real-time hardware, demonstrating the superior performance of COA-FOEMRAC as compared to various controllers. Thus, it can be effectively employed to improve the functionality of the magnetic joints and magnetic end effectors in real-time applications. A video demonstrating the functioning of the Maglev system is available at this link: https://drive.google.com/file/d/1FrD1YKqRXSTTe44S2-ap126KljiVmOEU/view?usp=drivesdk.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3285-3307"},"PeriodicalIF":5.2,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MINS: Efficient and Robust Multisensor-Aided Inertial Navigation System","authors":"Woosik Lee,&nbsp;Patrick Geneva,&nbsp;Chuchu Chen,&nbsp;Guoquan Huang","doi":"10.1002/rob.22546","DOIUrl":"https://doi.org/10.1002/rob.22546","url":null,"abstract":"<div>\u0000 \u0000 <p>Robust multisensor fusion of multi-modal measurements such as inertial measurement units (IMUs), wheel encoders, cameras, LiDARs, and GPS holds great potential due to its innate ability to improve resilience to sensor failures and measurement outliers, thereby enabling robust autonomy. To the best of our knowledge, this study is among the first to develop a consistent tightly-coupled Multisensor-aided Inertial Navigation System (MINS) that is capable of fusing the most common navigation sensors in an efficient filtering framework, by addressing the particular challenges of computational complexity, sensor asynchronicity, and intra-sensor calibration. In particular, we propose a consistent high-order on-manifold interpolation scheme to enable an efficient asynchronous sensor fusion and state management strategy (i.e., dynamic cloning). The proposed dynamic cloning leverages motion-induced information to adaptively select interpolation orders to control computational complexity while minimizing trajectory representation errors. We perform online intrinsic and extrinsic (spatiotemporal) calibration of all onboard sensors to compensate for poor prior calibration and/or degraded calibration varying over time. Additionally, we develop an initialization method with only proprioceptive measurements of IMU and wheel encoders, instead of exteroceptive sensors, which is shown to be less affected by the environment and more robust in highly dynamic scenarios. We extensively validate the proposed MINS in simulations and large-scale challenging real-world datasets, outperforming the existing state-of-the-art methods, in terms of localization accuracy, consistency, and computation efficiency. We have also open-sourced our algorithm, simulator, and evaluation toolbox for the benefit of the community: https://github.com/rpng/mins.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3252-3284"},"PeriodicalIF":5.2,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fault Detection and Diagnosis of Multi-Joint Manipulator Based on Multi-Information Fusion and Deep-Learning Machine Vision","authors":"Jinghui Pan","doi":"10.1002/rob.22583","DOIUrl":"https://doi.org/10.1002/rob.22583","url":null,"abstract":"<div>\u0000 \u0000 <p>The multi-joint manipulator with vision sensors has been widely used in real applications. However, the fault detection and diagnosis accuracy are lowered and the time expense is increased for the increased number of sensors, as there are many factors that are relative with this problem. This paper is focused on the fault detection and diagnosis problem of multi-joint manipulator, and the problem was divided into two sub-problems. The first is that the position estimation strategy based on data fusion of visual sensor and the position sensor was designed to carry out the fault detection, and the whether the faults had happened or not were determined by the position estimation errors. The second was focused on the fault diagnosis problem, where the deep convolutional neural network (DCNN) fault diagnosis model based on time-frequency mixed signal was constructed. The proposed DCNN uses the time and frequency domain information as its inputs and executes the classification tasks. The specific fault was determined through the output of DCNN model. The DCNN model was activated only when the first fault detection unit indicated that there was a fault, so the time expense was reduced from 5.3 to 2.6 s. The experiment based on the AUBO-i5 manipulator was carried out to evaluate the proposed fault detection and diagnosis model, where 10 categories of data sets that represent different working conditions of manipulator were adopted. The experimental results showed that the proposed multi-joint manipulator fault detection could improve the position estimation accuracy by 41.2%, and the fault diagnosis accuracy was improved by 20%.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3308-3322"},"PeriodicalIF":5.2,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, Modeling, and Control of a Personal Aerial System","authors":"Chen Lei,&nbsp;Dong Wei,&nbsp;Lv Yiqun,&nbsp;Gao Yongzhuo,&nbsp;Wu Dongmei,&nbsp;Dong Hui","doi":"10.1002/rob.22550","DOIUrl":"https://doi.org/10.1002/rob.22550","url":null,"abstract":"<div>\u0000 \u0000 <p>Miniature personal aerial vehicles (PAVs) with vertical take-off and landing (VTOL) capabilities offer significant advantages over conventional vehicles in rescue missions, particularly in terms of compactness, manned flight capability, and load-carrying capacity. However, detailed research work on such systems has been reported infrequently. This paper introduces a miniature VTOL PAV, weighing 55 kg and measuring 45 * 87 * 154 cm. The PAV is equipped with five vertically arranged micro-turbojet engines that enable VTOL capabilities and support a load capacity exceeding 100 kg. A two-degree-of-freedom vector nozzle mechanism attached to the engines allows precise thrust direction adjustments. Based on this propulsion system and the PAV's physical model, a cascade proportional-integral-derivative (PID) controller is developed to regulate PAV's position and attitude. Additionally, a feed-forward-based proportional-derivative (PD) controller is implemented to enhance the engine's thrust response. The PAV prototype underwent rigorous testing in various outdoor conditions, ranging from temperatures of −7°C to 42°C and wind speeds of 0 to 7.2 m/s. Experimental results show that the flight speed reached 14.65 m/s, with a flight duration exceeding 5 min. These results confirm the feasibility of the proposed PAV's design principles, demonstrating its adaptability to varying environmental conditions. While the primary focus of this paper is on the miniature PAV system, its findings contribute to the broader field of advanced air mobility research.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3227-3251"},"PeriodicalIF":5.2,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cascaded Extended-State-Observer-Based Synergetic Control for Quadcopter Translational Dynamics","authors":"Saif Sinan,&nbsp;Jawhar Ghommam,&nbsp;Maarouf Saad,&nbsp;Raouf Fareh,&nbsp;Maamar Bettayeb","doi":"10.1002/rob.22566","DOIUrl":"https://doi.org/10.1002/rob.22566","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper presents an approach to quadcopter position control, utilizing a Cascaded Extended State Observer (CESO) integrated with synergetic control. The proposed control strategy enhances the quadcopter's stability and tracking accuracy by estimating and compensating for aerodynamic disturbances and drag forces to a significant extent, which are challenging to measure or model analytically. This extent increases as the levels of the cascaded structure grow, progressively enhancing both accuracy and compensation capability. An efficient tuning approach is introduced in the paper for tuning multiple ESOs in a cascaded structure that uses hierarchical gain reduction, ensuring distinct frequency ranges for each observer. This achieves a rapid initial estimation while reducing noise in later stages, enhancing stability and robustness. The CESO framework, combined with synergetic control, offers a robust solution, minimizing mean squared error and control effort while improving disturbance rejection. The PX4-ROS2 architecture was used to test our system in Gazebo and on a custom-built quadcopter experimentally, validating the efficacy of the proposed control scheme. This study contributes significantly to the development of advanced control techniques for unmanned aerial vehicles, emphasizing practical implementation and adaptability in real-world scenarios.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3153-3171"},"PeriodicalIF":5.2,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Performance Analysis of an Autonomous Agricultural Vehicle for Fruit Transportation","authors":"Dilara Gerdan Koc,&nbsp;Mustafa Vatandas","doi":"10.1002/rob.22573","DOIUrl":"https://doi.org/10.1002/rob.22573","url":null,"abstract":"<p>Reducing product damage, preserving quality, and enhancing efficiency from harvest to consumption are crucial for sustainable agriculture. The integration of advanced information and communication technologies into agricultural practices plays a vital role in meeting these goals. This study introduces an autonomous transport vehicle designed for the efficient logistics of fruit transportation in agricultural settings<b>.</b> The vehicle's software framework is constructed on the Robot Operating System (ROS) and incorporates an enhanced hybrid navigation system that merges the Extended Kalman Filter (EKF) with Simultaneous Localization and Mapping (SLAM) for precise localization. The A* algorithm facilitates global path planning, whereas the Dynamic Window Approach (DWA) guarantees real-time obstacle avoidance. Essential hardware components comprise high-resolution LIDAR for environmental mapping, an Inertial Measurement Unit (IMU) for motion estimation, and wheel encoders for odometry. The performance evaluation was executed across five distinct terrain types: concrete, fine-tilled soil, coarse-tilled soil, asphalt, and grass. The vehicle attained optimal path-following precision on concrete, exhibiting a deviation of 5.39 cm at a speed of 0.3 m/s with a 200 kg payload, whereas tracking errors escalated on uneven terrains like grass and coarse-tilled soil. Maneuverability assessments verified a turning radius of 60.0 cm for 90° turns and 125.0 cm for 180° turns, ensuring suitability in restricted agricultural environments. Finite element analysis (FEA) evaluated structural durability under diverse loads (2000–4000 N), indicating a minimum safety factor of 1.23, thereby affirming structural stability under static conditions. This study demonstrates the potential of autonomous transport vehicles to revolutionize agricultural logistics by reducing labor dependency, improving operational efficiency, and supporting sustainable farming.</p>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3189-3212"},"PeriodicalIF":5.2,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rob.22573","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Robust Pose Estimation Method for Robot Grasping in Bin-Picking Scenarios Using Point Cloud","authors":"Yilin Lu,&nbsp;Tingting Wang,&nbsp;Kui Li","doi":"10.1002/rob.22571","DOIUrl":"https://doi.org/10.1002/rob.22571","url":null,"abstract":"<div>\u0000 \u0000 <p>Industrial robot grasping in bin-picking scenarios is challenging. This is mainly due to the need for robots to extract individual parts and find suitable grasping poses accurately and efficiently. This paper addresses this challenge by focusing on the complex morphology of injection-molded corner pieces and proposing a noise-robust pose detection model (NRP-Net) for suction-based grasping. We introduce a directional encoding module to enhance the perception of local structures. We also present an instance segmentation method based on differential features, which we integrate with pose space and visibility attention mechanisms to improve the accuracy of pose estimation. To ensure the correctness of the suction area, we design a sealing detection algorithm suitable for cluttered scenes. Validation in practical scenarios shows an 87.4% success rate in grasping. This demonstrates the effectiveness of our method in bin-picking scenarios and offers a viable solution for industrial robot grasping tasks.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3172-3188"},"PeriodicalIF":5.2,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Automatic Docking System of LNG Marine Loading Arm Based on Machine Vision","authors":"Zhicheng Ma,&nbsp;Yonghua Lu,&nbsp;Chuan Huang,&nbsp;Shigong Feng,&nbsp;Jing Chen","doi":"10.1002/rob.22579","DOIUrl":"https://doi.org/10.1002/rob.22579","url":null,"abstract":"<div>\u0000 \u0000 <p>Liquefied Natural Gas is widely used as a clean energy source in production and daily life. The transfer of LNG between receiving terminals and cargo ships is accomplished using LNG marine loading arms. During the loading and unloading of LNG, the flange position on the LNG ship is typically determined manually, and the connection is controlled manually as well. This method is inefficient, dangerous, and its success rate and accuracy do not meet the demands of modern productivity. Moreover, there is limited research on the automatic docking system of LNG marine loading arm and their docking accuracy is not high. To address the need for automated docking of loading arms, this paper proposes a two-step positioning method, combining coarse positioning and fine positioning. It integrates deep learning, edge detection algorithms, and ellipse fitting algorithms to obtain the image coordinates of the flange center. The motion trajectory of the loading arm's end is planned and automatic docking is achieved through PID control. Through testing at the established experimental site, the system achieves a port recognition accuracy of 99.99%, with the maximum docking error of 7.79 mm and the average error of 5.80 mm, thus validating the feasibility of automatic docking for LNG loading arms.</p>\u0000 </div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3213-3226"},"PeriodicalIF":5.2,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, Analysis, and Flexibility Evaluation of a Double-Mode Underactuated Coupled-Drive Omnidirectional Mobile Robot","authors":"Zhiguo Lu,&nbsp;Yulong Ren,&nbsp;Chong Liu,&nbsp;Siyang Chen,&nbsp;Yiheng Zhao","doi":"10.1002/rob.22574","DOIUrl":"https://doi.org/10.1002/rob.22574","url":null,"abstract":"<div>\u0000 \u0000 <p>Current omnidirectional mobile robots often utilize Mecanum wheels, omnidirectional wheels, or steering wheels, but these technologies present certain operational limitations. This paper investigates a double-mode underactuated coupled-drive omnidirectional mobile robot to improve adaptability and flexibility across various terrains. By designing a double-crank linkage and cross-slider mechanism, the robot achieves omnidirectional translation and in-place rotation modes without using the steering wheel. In the translation mode, the four wheels act as an integrated system, always remaining parallel; in the rotation mode, each wheel can independently rotate around its respective yaw axis, enabling the robot to rotate. This structure significantly reduces the turning radius of the robot. By utilizing the cross slider in conjunction with limit blocks, the relative positions of the double connecting rods are constrained, ensuring the robot maintains a constant posture during omnidirectional movement and resolving the uncertainty and dead-center position issues in the double-crank connecting rod motion process. The omnidirectional mobile robot studied in this paper has applied for a patent. To validate the feasibility of the robot's motion modes, structural analysis, dynamic analysis, and kinematic analysis were conducted, and the stability and flexibility of the robot were verified through physical experiments.</p></div>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3138-3152"},"PeriodicalIF":5.2,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Path Planning Algorithm Based on Tangent Point Search and Constrained B-Spline","authors":"Ge Tai,&nbsp;Chaoyi Dong,&nbsp;Shuai Xiang,&nbsp;Tianyu Yuan,&nbsp;Haoda Yan,&nbsp;Qilai Wang,&nbsp;Xiaoyan Chen","doi":"10.1002/rob.22570","DOIUrl":"https://doi.org/10.1002/rob.22570","url":null,"abstract":"<p>The traditional Tangent Point Search (TPS) algorithm, as a path planning algorithm suitable for large-scale maps, performs well in the presence of large rectangular obstacles. However, it has two disadvantages: 1. it requires that the obstacles be rectangular so that the shape of obstacles is limited to the fixed form. 2. its resulting path does not meet the curvature constraints of vehicles so that it makes vehicles difficult to be tracked smoothly. To expand its scope of application, this paper categorizes obstacles into three types: polygonal obstacles, linear obstacles, and point obstacles. Based on this classification, a TPS+B algorithm is proposed to improve its ability to determine the tangent point cells in the TPS algorithm by convexifying the obstacles. To solve the problem of limited obstacle shapes, the cell coordinates of obstacle vertices are extended to the coordinates of convex hull vertices when the obstacles are arbitrary shapes. When using the B-spline algorithm for trajectory smoothing, the situation where the curved trajectory intersects with obstacles may occur. To avoid such a situation, the locally optimized path planning is designed by incorporating obstacle avoidance constraints and curvature constraints. The aim of such a design is to shift the path points of the TPS algorithm, thereby obtaining a collision-free trajectory that satisfies the vehicle's curvature constraints. Without considering the constraint of path curvature, a comparison of the A*, Dijkstra, Rapidly-exploring Random Tree (RRT), Jump Point Search (JPS), and the improved TPS algorithms reveals that the improved TPS algorithm achieves optimal performance in both algorithm time and path length. Specifically, in the large-scale map, the algorithm time is reduced by 69.16% compared to JPS, and the path length is shortened by 3.47% compared to Dijkstra. In the small-scale map, the algorithm time is reduced by 39.16%, and the path length is shortened by 1.27%. When considering the constraint of path curvature, a comparison between the Dynamic Window Approach (DWA) and Hybrid A* algorithms further demonstrates that the TPS+B algorithm remains optimal in both algorithm time and path length. In this scenario, in the large-scale map, the algorithm time is decreased by 97.56% compared to DWA, and the path length is reduced by 2.02% compared to Hybrid A*. In the small-scale map, the algorithm time is decreased by 61.9%, and the path length is reduced by 3.68%. The experimental results confirm the superiority of the TPS+B algorithm in path planning for different scale maps with various obstacles.</p>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3121-3137"},"PeriodicalIF":5.2,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rob.22570","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}