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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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Graphene photodetectors integrated with silicon and perovskite quantum dots

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Microsystems & Nanoengineering 2024年第3期10卷 21-33页

作者： Kashif Abbas Peirui Ji Naveed Ullah Shareen Shafique Ze Zhang Muhammad Faizan Ameer Shenghan Qin Shuming Yang State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049China Department of Microelectronic Science and Engineering Laboratory of Clean Energy Storage and ConversionSchool of Physical Science and TechnologyNingbo Collaborative Innovation Center of Nonlinear Calamity System of Ocean and AtmosphereNingbo UniversityNingbo 315211China

Photodetectors(PDs)play a crucial role in imaging,sensing,communication systems,***(Gr),a leading two-dimensional material,has demonstrated significant potential for photodetection in recent ***,its relatively weak interaction with light poses challenges for practical *** integration of silicon(Si)and perovskite quantum dots(PQDs)has opened new avenues for Gr in the realm of next-generation *** review provides a comprehensive investigation of Gr/Si Schottky junction PDs and Gr/PQD hybrid PDs as well as their *** operating principles,design,fabrication,optimization strategies,and typical applications of these devices are studied and *** these discussions,we aim to illuminate the current challenges and offer insights into future directions in this rapidly evolving field.

关键词： quantum discussions summarized

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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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Aerodynamic Analysis and Deployment Mechanism of A Foldable Mars Quadrotor

Aerodynamic Analysis and Deployment Mechanism of A Foldable ...

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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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Analysis of spectrum spread interference pulse compression output based on stationary phase method 6

Analysis of spectrum spread interference pulse compression o...

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6th International Conference on Information Science, Electrical, and Automation Engineering, ISEAE 2024

作者： Zhang, Kaiyu Wu, Qihua Zhao, Feng Zhao, Tiehua Wang, Yanfeng Liu, Xiaobin State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781510682924

To study the time-domain characteristics of spectrum-spread interference after matched filtering, this paper uses the stationary phase method to estimate its time-domain output. Then, the interference signal is simulated by matched filtering operation to obtain the corresponding pulse compression results, which are similar to the estimated results of the stationary phase method. The results show that the stationary phase method is a simple and effective way to analyze the pulse compression properties of spectrum-spread interference signals. © 2024 SPIE.

关键词： Matched filters

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Jamming Detection Based on Phase Feature for SAR Images

Jamming Detection Based on Phase Feature for SAR Images

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2023 International Conference on Algorithm, Imaging Processing, and Machine Vision, AIPMV 2023

作者： Zhang, Haoyu Quan, Sinong Xing, Shiqi Liu, Yitao State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System National University of Defense Technology Hunan Changsha China

ISBN: (纸本)9781510672444

Synthetic Aperture Radar (SAR) is capable of producing high-resolution complex-valued pictures, which have extensive applications in both civil and military domains. Among these applications, SAR electronic countermeasures currently represent a prominent area of research interest. Presently, within the radar electronic countermeasures, there exists a diminishing disparity among the features of real and false targets, rendering the detection of jamming increasingly challenging. This paper examines the phase of SAR images and presents a method for identifying SAR jamming regions based on phase features. The initial step involves organizing the cluttered phase information into neighborhood phase differences. Subsequently, this information is coupled with the amplitude to obtain the weighted phase difference. This metric effectively captures the extent of phase distortion resulting from jamming. The findings from the simulation experiment demonstrate that the proposed feature and method are capable of accurately identifying and filtering out the jamming region in SAR pictures. Furthermore, it demonstrates the prospection of phase within the SAR image interpretation and electronic countermeasures. © 2024 SPIE.

关键词： Synthetic aperture radar

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A Two-Step Approach for Multi-topology Identification and Parameter Estimation of Power Distribution Networks

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CSEE Journal of Power and Energy systems 2024年第6期10卷 2446-2456页

作者： Li Ma Lei Wu Nian Liu Wei Pei Institute of Electrical Engineering and Key Laboratory of Long-Duration and Large-Scale Energy StorageChinese Academy of SciencesBeijing 100190China Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ 07030USA State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources North China Electric Power UniversityBeijing 102206China

To improve observability in power distribution networks(PDN),a two-step framework of multi-topology identification and parameter estimation is proposed in this ***,in the first step,a mixed-integer linear program(MILP)model-based split method is proposed to recognize mixed topologies in a multi-record dataset without a prerequisite on the number of topology categories and values of nodal voltage phase *** the second step,line parameters and nodal voltage phase angles are estimated using the Newton-Raphson method based on nodal measurements of real and reactive power injections,as well as voltage ***,a modified estimation model is proposed to apply to the multitopology ***,case studies on an IEEE 33-bus system illustrate the effectiveness of the proposed models in identifying the PDN’s topologies,as well as estimating line parameters and voltage phase angles.

关键词： MILP Newton-Raphson method parameter estimation power distribution system topology identification

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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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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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