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Research on Surface Defect Detection Technology of Long-Distance and Long-Span FAST Cable

Research on Surface Defect Detection Technology of Long-Dist...

引用

Mechatronics and robotics Engineering (ICMRE), International Conference on

作者： Xin Tong Xuehe Zhang Gangfeng Liu Changle Li Jie Zhao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

Aiming at the problems of large cable span, small number of defect samples and complex background environment in the FAST cable defect detection task, a set of real-time defect detection algorithms based on convolutional neural network is proposed to realize the accurate location and classification of defects. It can achieve a good detection effect for defects with multiple angles and sizes, especially suitable for medium and long distances. The algorithm is verified on the dataset, and its recognition accuracy can reach 91.7%. Equipped on the hardware inference platform, it fully meets the efficiency and accuracy requirements of FAST cable inspection site, can be used in actual cable quality inspection tasks, and can be widely promoted to real-time defect detection of various high-altitude hanging cables.

关键词： Mechatronics Simulation Inspection Real-time systems Inference algorithms Hardware Convolutional neural networks

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A novel design of force-feedback master manipulator for remote ultrasound scanning

A novel design of force-feedback master manipulator for remo...

引用

2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Li, Changle Zhang, Chentao Yu, Chuan You Zhang, Leifeng Liu, Gangfeng Zhao, Jie Harbin Institute of Technology State Key Laboratory of Robotics and System No.2 YiKuang Street NanGang District Harbin HeiLongJiang China

ISBN: (纸本)9781665481090

This paper presents a novel six-degree-of-freedom force feedback master manipulator for remote ultrasound scanning. Firstly, a new configuration based on a planar five-link mechanism is proposed, taking into account the practical needs of medical ultrasound scanning. This configuration has two operating modes and can provide three degrees of force feedback. Secondly, a hybrid force/position master-slave control system based on the kinetic model force feedback method is built, which can realize incremental master-slave control, variable proportional control, force feedback, and other functions. Finally, the positional accuracy, gravity balance effect, and force feedback performance of this master manipulator are verified through experiments. Experiments show that the average position error of this novel force feedback master manipulator is 1.18 mm, the average attitude error expressed in terms of Euler angles is 0.83°, and the maximum feedback force that can be provided is 12.1 N, which satisfies the requirements of ultrasonic scanning. © 2022 IEEE.

关键词： Feedback

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A Novel Approach for Solving Time-Varying Linear Equations and Its Application in Motion Tracking of Redundant Robots

A Novel Approach for Solving Time-Varying Linear Equations a...

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Frontiers of robotics and Software Engineering (FRSE), International Conference on

作者： Hong Yin Hongzhe Jin Jie Zhao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

Solving time-varying linear equations is a common problem in many fields. In this article, a novel approach is proposed based on the cost function constructed by the mixed error, which is made up of the residual error and its integration. The merits of the novel approach include high accuracy, noise immunity, and asymptotic convergence. Since the derivative information of time-varying signals is used in the proposed method, a proportional-integral differentiator is designed based on the mixed estimation error for the first derivative estimation. The proposed differentiator has a high degree of precision, asymptotic convergence, and no chattering. In addition, theoretical analyses prove the convergence of the proposed optimal strategy and differentiator. Simulation results validate the effectiveness and superiority of the proposed strategy and the designed differentiator. Finally, the proposed approach is employed in the motion tracking of redundant robots.

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A Kinematic Decoupling Whole-body Control Method for a Mobile Humanoid Upper Body Robot

A Kinematic Decoupling Whole-body Control Method for a Mobil...

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Frontiers of robotics and Software Engineering (FRSE), International Conference on

作者： Fengjia Ju Hongzhe Jin Jie Zhao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

The mobile humanoid upper body robot combines the humanoid upper body robot with the mobile platform. It has high redundancy and can complete complex tasks. However, coupling joints, including the waist joints and the mobile platform, exist in the configuration of the robot. During the task execution, the motion of the end-effectors on the dual arms are not independent, but interfere with each other through the motion of the waist and the mobile platform. Therefore, we need to decouple the waist and mobile platform from the dual arms. Based on the pseudo-inverse method of the redundant manipulators, we consider the motion of the coupling joints as a disturbance term and propose a kinematic decoupling whole-body control method. The method realizes the decoupling and cooperation of dual arms, avoids the interference of the inverse kinematics model of the dual arms, and fully releases the application potential of the high redundancy. The decoupling method allows the waist joints and the mobile platform to move randomly without affecting the task operation at the end-effectors, and to further plan their movements separately in order to smooth the whole body motion. The simulations on the mobile humanoid upper body robot verifies our method.

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Data Augmentation for Improving CNNs in Medical Image Classification

Data Augmentation for Improving CNNs in Medical Image Classi...

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6th International Conference on Intelligent Computing and Signal Processing (ICSP)

作者： Yi Ren Zengmin He Yang Deng Bo Huang State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

Medical image is essential for physicians to diagnose diseases. And convolutional neural networks (CNNs) have gained momentum for computer-aided diagnosis (CAD) medical image. However, there are still challenges in CNNs related to a lack of data and class-imbalanced datasets. Data augmentation is utilized to address the issues mentioned above. In this study, the Pseudo-color enhancement algorithm (OCEAN and TWILIGHT), common linear transform, CLAHE enhancement, and K-means clustering algorithm were applied to pneumonia X-ray images for data augmentation. Thus, five processed datasets were finally obtained. The results indicated that five data-augmentation methods effectively improved the performance of CNNs for the pneumonia X-ray images binary classification detection, in which the CLAHE enhancement and OCEAN enhancement methods had the accuracy and F1 Score with 97.42%, 97.19%, and 97.42%, 98.36%, respectively. DenseNet121 showed the best classification performance of four CNNs utilized in this study, as evidenced by the area under the receiver operating characteristic (ROC) curves (AUC). To verify the generalizability of the two enhancement methods, CLAHE and OCEAN enhancement methods were applied to the Magnetic Resonance Imaging (MRI) dataset of Alzheimer's disease, which had the accuracy and F1 Score with 98.15% , 98.15%, and 97.22%, 97.68%, respectively. Therefore, these simple and efficient data-augmentation methods effectively improve the performance of CNNs for diagnosing medical image, which can provide theoretical reference for physicians to diagnose the above two diseases, and advance the application of clinical medicine.

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Aerodynamic Analysis and Deployment Mechanism of A Foldable Mars Quadrotor

Aerodynamic Analysis and Deployment Mechanism of A Foldable ...

引用

IEEE International Conference on Mechatronics and Automation

作者： Kaijie Zhu Dewei Tang Qiquan Quan Kaiyi Wang Yachao Dong Zongquan Deng State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

The Mars quadrotor is a vertical take-off and landing aerial platform developed to enhance the efficiency of Mars exploration. The four-blade rotor has a high thrust coefficient due to its high solidity, which enables the quadrotor to navigate the Martian atmospheric environment efficiently. This paper proposes a payload-carrying Mars quadrotor featuring four four-bladed rotors that can fold along the rotor arms. The computational fluid dynamics (CFD) method is employed to perform numerical hovering simulations, exploring the propulsion capability and aerodynamic efficiency of rotors with different diameters. The mass distribution and hovering time are estimated when the quadrotor consists of the rotors with the highest figure of merit. The results demonstrate that a larger rotor diameter of the quadrotor yields greater payload capacity and shorter hovering time. During the launch, the quadrotor is folded and constrained within an envelope to protect it from vibrations and shocks. A lifting mechanism with shape-constraint slides is utilized for quadrotor deployment.

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Design and Implementation of Quasi-Direct-Drive Legs for a Frog-Like Jumping Robot

Design and Implementation of Quasi-Direct-Drive Legs for a F...

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Computer, Control and robotics (ICCCR), International Conference on

作者： Dong Zhihui Fan Jizhuang Du Qilong Zhao Jie State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

This study aims to design and optimize a motor-driven frog-like jumping robot leg for efficient vertical jumps and multiple consecutive horizontal jumps. We have conducted bionic research on frog legs' structure and motion characteristics and further explored their motion mechanism, providing new ideas and methods for designing and manufacturing robots with high mobility and adaptability. First, our research team designed a robot leg prototype based on the frog's body structure, optimized the robot using computer-aided design software, and selected a suitable motor-driven actuator. Secondly, the weight reduction optimization of the robot body is carried out regarding material selection and topology optimization to improve the robot's maneuverability and jump height. Finally, after manufacturing the prototype of the robot legs, the robot is experimentally verified. The results show that the robot legs can achieve efficient vertical jumps (the maximum height is 1.40 meters, about 7.8 times the length of the leg link). It can also jump multiple times consecutively, which is significant for applying robots in dangerous environments, search and rescue, and other fields.

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A Positioning Method Based on Kalman Filter for FAST Feed Support Cable Inspection Robot

A Positioning Method Based on Kalman Filter for FAST Feed Su...

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Mechatronics and robotics Engineering (ICMRE), International Conference on

作者： Xiangyu Sun Gangfeng Liu Xuehe Zhang Changle Li Jie Zhao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

In this paper, a positioning system developed for cable inspection robot system which works on feed support cables of Five-hundred-meter Aperture Spherical radio Telescope (FAST) is introduced. The positioning system consists of wheeled odometers and a Real-tme kinematic (RTK) based Global Navigation Satellite system (GNSS). Firstly, the cable with fixed ends and free suspension in the middle is modeled, and the influence of wind on the cable in FAST site is analyzed. Then, the data of the four odometers on the robot are processed, and the odometer information is fused with GNSS information through Kalman filtering. Then the best position estimation of the cable inspection robot is determined. A simulation is finally established to verify the proposed robot positioning method. The result shows that the method can work pretty well under the real working situation.

关键词： Vibrations Global navigation satellite system Analytical models Solid modeling Inspection Mathematical models Feeds

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Structural Design and Experiment of a Small Wheel-legged Mobile Robot with Variable Configuration

Structural Design and Experiment of a Small Wheel-legged Mob...

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IEEE International Conference on Mechatronics and Automation

作者： Xiulong Cui Jizhuang Fan Zhihui Dong Yue Ou Jie Zhao The State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

In this paper, we made an improved design on the traditional quadruped robot structure and developed a new small wheel-legged mobile robot structure. It has four legged configurations, which can be selected according to different situations, improving the mobility and operability of the robot. In wheeled mode, the robot can adjust its center of gravity according to actual needs. Including the rotational degree of freedom of the wheel, each leg has four degrees of freedom. Each leg adopts a series structure and moves the knee drive motor to the fuselage position using a parallel four-link mechanism and is symmetrically arranged with the hip drive motor. A wheel is installed at the end of the shank, and a DC brushless motor is built inside it, enabling the robot to have the function of wheeled motion. This article introduces the details of the wheel-legged robot, emphasizing the innovative design of the physical structure and the diversity of deformation. The forward kinematics was analyzed. Based on the full-elbow configuration (a type of legged configuration), a cycloidal motion optimization simulation was completed for the single leg structure. Simulation experiment has proven that the optimized robot’s single leg motion is smoother. Finally, we conducted a typical experiment using an embedded controller to control single leg motion. The experimental results verify that the optimized cycloidal motion of the robot meets the desired motion effect.

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Optimizing Dataset Configuration for Improving Convolutional Neural Networks Performance in Chest X-ray Image Classification

Optimizing Dataset Configuration for Improving Convolutional...

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6th International Conference on Intelligent Computing and Signal Processing (ICSP)

作者： Zengmin He Yi Ren Honggang Wang State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

Chest X-ray (CXR) is essential for physicians to diagnose lung diseases in clinical medicine. With the development of computer and deep learning techniques, creating CXR datasets to train convolutional neural networks (CNNs) has become a popular research topic. However, there are still challenges in creating datasets due to class imbalance and the ratio setting of datasets. This study investigated the impact of class imbalance and the ratio of training, validation, and test sets on CNNs classification performance by optimizing the dataset configuration. This was achieved by directly modifying the ratio, applying oversampling based on the adaptive contrast enhancement (ACE) algorithm, and random undersampling to balance the dataset classes, followed by modifying the ratio again. Therefore, seven datasets were obtained, which were utilized to individually train four CNNs based on transfer learning and fine-tuning techniques. Evaluation metrics based on the confusion matrix were utilized to demonstrate the enhanced classification performance of CNNs. The results indicated that at least 17% of the accuracy of CNNs trained by the dataset with modified ratios was improved as compared with the dataset with an unreasonable initial configuration. Additionally, the overall evaluation metrics of CNNs were further improved by balancing the dataset classes and modifying the ratios. ChexNet demonstrated the best classification performance among the four CNNs, as evidenced by the area under the receiver operating characteristic (ROC) curves (AUC). Furthermore, ChexNet was trained by a class balanced dataset with a ratio of 7:2:1, resulting in the best evaluation metrics, including F1 Score, balanced accuracy, accuracy, recall, specificity, and precision, which were 97.81%, 97.78%, 97.78%, 98.73%, 96.84%, and 96.89%, respectively. Therefore, optimizing dataset configuration can effectively improve the performance of CNNs, providing empirical guidance for researchers in creating dat

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