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Boosting the Efficiency and Mechanical Stability of Organic Solar Cells Through a Polymer Acceptor by Reducing the Elastic Modulus

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Advanced Energy Materials 2025年

作者： Wang, Yan Yu, Han Zhao, Dan Liu, Wei Liu, Baoze Wu, Xin Gao, Danpeng Zhang, Dong Zhang, Shoufeng Sun, Xianglang Zhang, Chunlei Zhao, Chaoyue Fu, Yuchen Song, Wei Gong, Shaokuan Fu, Yuang Kwok, Chung Hang Ge, Ziyi Lu, Xinhui Chen, Xihan Xiao, Shuang Wong, Wai-Yeung Chai, Yu Yan, He Zhu, Zonglong Department of Chemistry City University of Hong Kong Kowloon999077 Hong Kong Department of Chemistry Guangdong-Hong Kong-Macao Joint Laboratory of Optoelectronic and Magnetic Functional Materials Energy Institute and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration & Reconstruction Hong Kong University of Science and Technology Clear Water Bay Kowloon999077 Hong Kong Department of Applied Biology and Chemical Technology and Research Institute for Smart Energy The Hong Kong Polytechnic University Hung Hom 999077 Hong Kong Hong Kong University of Science and Technology-Shenzhen Research Institute No. 9 Yuexing 1st RD Hi-tech Park Nanshan Guangdong Shenzhen518057 China School of Automation Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China Department of Physics City University of Hong Kong Kowloon999077 Hong Kong Zhejiang Engineering Research Center for Energy Optoelectronic Materials and Devices Ningbo Institute of Materials Technology & Engineering Chinese Academy of Sciences Ningbo315201 China Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems SUSTech Energy Institute for Carbon Neutrality Department of Mechanical and Energy Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China Department of Physics The Chinese University of Hong Kong Shatin999077 Hong Kong Center for Advanced Material Diagnostic Technology and College of Engineering Physics Shenzhen Technology University Guangdong Shenzhen518118 China Shenzhen Research Institute City University of Hong Kong Shenzhen518057 China

Organic solar cells (OSCs) are regarded as one of the most promising flexible power sources due to their lightweight and flexible properties, with the improvement of photovoltaic and mechanical performance. To improve the current density and power conversion efficiency (PCE), mPh4F-TS (TS) and PYSe2F-T (PA) are introduced into the binary host, PM6/mPh4F-TT (PM6/TT) as third components. It is demonstrated that the corresponding ternary devices, in both rigid and flexible devices, achieved superior efficiencies (19.6%/17.7% for PM6/TT+TS, and 19.2%/17.4% for PM6/TT+PA) outperform the binary counterparts (18.3%/16.4%). However, distinct differences in mechanical performance are observed between the polymer acceptor (PA) and small-molecular acceptor (TS). The PM6/TT+PA significantly improved the mechanical stability of flexible devices with a lower elastic modulus of 3.6 GPa, while the PM6/TT+TS resulted in the opposite effect with a higher elastic modulus of 5.5 GPa. Through in-depth investigation, a clear correlation between the elastic modulus, crack density, and mechanical stability of the active layer blends is successfully established, revealing the key role of reducing the elastic modulus in enhancing the mechanical stability of flexible OSCs. This study provides important guidance for the development of flexible photovoltaic devices with both high efficiency and mechanical robustness. © 2025 The Author(s). Advanced Energy Materials published by Wiley-VCH GmbH.

关键词： Organic solar cells

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3D Part Guided Image Editing for Fine-Grained Object Understanding

3D Part Guided Image Editing for Fine-Grained Object Underst...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zongdai Liu Feixiang Lu Peng Wang Hui Miao Liangjun Zhang Ruigang Yang Bin Zhou State Key Laboratory of Virtual Reality Technology and Systems Beihang University Robotics and Autonomous Driving Laboratory Baidu Research National Engineering Laboratory of Deep Learning Technology and Application China ByteDance Research University of Kentucky Peng Cheng Laboratory Shenzhen China

ISBN: (数字)9781728171685

ISBN: (纸本)9781728171692

Holistically understanding an object with its 3D movable parts is essential for visual models of a robot to interact with the world. For example, only by understanding many possible part dynamics of other vehicles (e.g., door or trunk opening, taillight blinking for changing lane), a self-driving vehicle can be success in dealing with emergency cases. However, existing visual models tackle rarely on these situations, but focus on bounding box detection. In this paper, we fill this important missing piece in autonomous driving by solving two critical issues. First, for dealing with data scarcity, we propose an effective training data generation process by fitting a 3D car model with dynamic parts to cars in real images. This allows us to directly edit the real images using the aligned 3D parts, yielding effective training data for learning robust deep neural networks (DNNs). Secondly, to benchmark the quality of 3D part understanding, we collected a large dataset in real driving scenario with cars in uncommon states (CUS), i.e. with door or trunk opened etc., which demonstrates that our trained network with edited images largely outperforms other baselines in terms of 2D detection and instance segmentation accuracy.

关键词： Three-dimensional displays Automobiles Solid modeling Two dimensional displays Image segmentation Vehicle dynamics Training

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Design and analysis of a flying-crawling spherical robot for multi-mode movement

Design and analysis of a flying-crawling spherical robot for...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Lu, Pengfei Xu, Kun Ding, Xilun Jiang, Shuiqing Tang, Zixin Wang, Yaobing Beihang University Robotics Institute of School of Mechanical Engineering and Automation Beijing China Beijing Institute of Spacecraft System Engineering Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing China

ISBN: (纸本)9781728163215

A novel spherical robot named flying-crawling spherical robot is designed in this paper. It can fly or roll on ground with its single rotor and eight tail fins. When its limbs stretch out it can crawl on the supporting surface. Besides, with its limbs the robot can realize carrying objects, landing on uneven ground and walking on the supporting surface. Dynamic model of the robot in flight mode is established and the motion characteristics are analyzed. A PID control system is designed to enable the robot to achieve stable flight. Trot gait planning of the robot is given and a PID controller is designed for tail fins assistant in crawling mode. Corresponding simulations are carried out and the simulation results verify the proposed methods. © 2019 IEEE.

关键词： Three term control systems

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HybrUR: A Hybrid Physical-Neural Solution for Unsupervised Underwater Image Restoration

arXiv

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arXiv 2021年

作者： Yan, Shuaizheng Chen, Xingyu Wu, Zhengxing Tan, Min Yu, Junzhi The Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Chinese Academy of Sciences Beijing100190 China The Department of Mechanical Engineering Fuzhou University Fuzhou350000 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Xiaobing.AI Beijing100080 China The State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China

Robust vision restoration of underwater images remains a challenge. Owing to the lack of well-matched underwater and in-air images, unsupervised methods based on the cyclic generative adversarial framework have been widely investigated in recent years. However, when using an end-to-end unsupervised approach with only unpaired image data, mode collapse could occur, and the color correction of the restored images is usually poor. In this paper, we propose a data- and physics-driven unsupervised architecture to perform underwater image restoration from unpaired underwater and in-air images. For effective color correction and quality enhancement, an underwater image degeneration model must be explicitly constructed based on the optically unambiguous physics law. Thus, we employ the Jaffe-McGlamery degeneration theory to design a generator and use neural networks to model the process of underwater visual degeneration. Furthermore, we impose physical constraints on the scene depth and degeneration factors for backscattering estimation to avoid the vanishing gradient problem during the training of the hybrid physical-neural model. Experimental results show that the proposed method can be used to perform high-quality restoration of unconstrained underwater images without supervision. On multiple benchmarks, the proposed method outperforms several state-of-the-art supervised and unsupervised approaches. We demonstrate that our method yields encouraging results in real-world applications. © 2021, CC BY-NC-ND.

关键词： Image reconstruction

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Micro Robotic Manipulation System for the Force Stimulation of Muscle Fiber-like Cell Structure

Micro Robotic Manipulation System for the Force Stimulation ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Xie Chen Qing Shi Shingo Shimoda Tao Sun Huaping Wang Qiang Huang Toshio Fukuda Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Intelligent Behavior Control Collaboration Unit RIKEN Center of Brain Science Nagoya Japan Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Many previous works have facilitated muscle cell (C2C12) alignment to form fiber-like cell structures. However, there still remains a challenge how to induce C2C12 myoblasts in the cell structures to differentiate into matured myocytes to form a functional muscle tissue, while external mechanical stimulation has been proved to have good effects on proliferation and differentiation of myoblasts. In this paper, we proposed a vision-based micro robotic manipulation system to achieve automatic mechanical stimulation for one single muscle fiber-like cell structures (MFCS). A tube, which is attached to a three degree-of-freedom (DOF) manipulator, and a probe are employed to apply the uniaxial mechanical stimulation to train the MFCS. To measure the force applied on MFCS, a vision-based measuring and correction method is utilized, which decrease the error by 74%. Moreover, based on the viscoelastic property of the MFCS, a feedback control algorithm has been applied to compensate for the force loss to realize the force stimulation. And the final value of force remains 699 ± 1μN after 110s experiment.

关键词： Force measurement Force Measurement uncertainty Muscles Manipulators Feedback control Electron tubes

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Online Parameter Estimation For Uncertain Robot Manipulators With Fixed-time Convergence

Online Parameter Estimation For Uncertain Robot Manipulators...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Chengzhi Zhu Yiming Jiang Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China National Engineering Laboratory for Robot Visual Perception and Control Hunan University Changsha China Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

For traditional parameter estimation schemes of uncertain robot, most of them were proposed to identify unknown parameter with desired precision, but few of them focused on the convergence time. Recently finite-time estimation techniques have been proposed by scholars to achieve estimation in finite time. In this paper, we proposed a novel estimation scheme for uncertain robot systems with fixed time instead of finite time. In order to avoid using acceleration signals during the estimation, a kind of auxiliary filtering technique was employed. Besides, a continuous and recursive update law was employed for the parameter estimation such that the computational burdens of real-time inversion of square matrices could be avoided. Finally the effectiveness of the identification algorithm is verified based on a 2-DOF uncertain robot model.

关键词： Parameter estimation Filtering Heuristic algorithms Estimation Real-time systems Manipulator dynamics Convergence

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Fundus-Image-Based Retinal Vascular Analysis in Myopic Eyes

Fundus-Image-Based Retinal Vascular Analysis in Myopic Eyes

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Chinese Control Conference (CCC)

作者： Jichen Shen Haohan Zou Yan Wang Jinchao Liu Ningbo Yu College of Artificial Intelligence Nankai University Tianjin China Clinical College of Ophthalmology Tianjin Medical University Tianjin China Tianjin Key Lab of Ophthalmology and Visual Science Tianjin Eye Institute Tianjin Eye Hospital Nankai University Affiliated Eye Hospital Tianjin China Nankai University Eye Institute Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

Myopia is prevalent worldwide and it is of great significance to prevent, control and intervene myopia in an early stage. The etiopathogenesis of myopia remains unclear and needs further research. Fundus photographs can show biomarkers and lesions of the retina in a non-invasive way directly. To discover some potential changes in myopic eyes, we extracted the retinal vascular features from vessel segmented results, and calculated the Spearman correlation coefficients between the retinal vascular features and the spherical refractive errors. The Kruskal-Wallis test was applied to explore the difference exists in the characteristics of retinal vessels among the mild, moderate and high myopia groups. The statistical analysis results indicated that the higher the degrees of myopia, the smaller the retinal vessels. This study found vascular changes in myopic eyes through fundus images, which could help to explain the mechanism of myopia and the damage caused by myopia.

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Stiffness Estimation and Intention Detection for Human-Robot Collaboration

Stiffness Estimation and Intention Detection for Human-Robot...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Xiongjun Chen Yiming Jiang Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China National Engineering Laboratory for Robot Visual Perception and Control Hunan University Changsha China Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

In this paper, we propose a stiffness estimation and intention detection method for human-robot collaboration. The human arm endpoint stiffness can be obtained according to the muscle activation levels of the upper arm and the human arm configurations. The estimated endpoint stiffness of human arm is matching to the robot arm joint stiffness through an appropriate mapping. The motion intention of human arm is detected based on the wrist configuration which is recognized by a Myo armband attached at the forearm of the operator. In order to reduce the time of feature engineering to ensure the performance of real-time collaboration, the wrist configuration recognition is realised based on the neural learning algorithm. The sEMG of the human forearm is directly fed into the neural network after processing by filters and sliding windows. The force sensor at the end of the robot arm is embedded in the feedback loop to make the robot arm better adapted to the operator's movement. The results of experiments performed on Baxter robot platform illustrate a good performance and verifies the proposed method.

关键词： Wrist Neural networks Collaboration Estimation Robot sensing systems Manipulators Robots

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Mapping Surgeons Hand/Finger Movements to Surgical Tool Motion during Conventional Microsurgery Using Machine Learning

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Journal of Medical robotics Research 2021年第3-4期6卷

作者： Fattahi Sani, Mohammad Ascione, Raimondo Dogramadzi, Sanja Bristol Robotics Laboratory University of the West of England Bristol United Kingdom Bristol Heart Institute and Translational Biomedical Research Centre Faculty of Health Science University of Bristol Bristol United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Sheffiled United Kingdom

Purpose: Recent developments in robotics and artificial intelligence (AI) have led to significant advances in healthcare technologies enhancing robot-Assisted minimally invasive surgery (RAMIS) in some surgical specialties. However, current human-robot interfaces lack intuitive teleoperation and cannot mimic surgeon's hand/finger sensing required for fine motion micro-surgeries. These limitations make teleoperated robotic surgery not less suitable for, e.g. cardiac surgery and it can be difficult to learn for established surgeons. We report a pilot study showing an intuitive way of recording and mapping surgeon's gross hand motion and the fine synergic motion during cardiac micro-surgery as a way to enhance future intuitive teleoperation. Methods: We set to develop a prototype system able to train a Deep Neural Network (DNN) by mapping wrist, hand and surgical tool real-Time data acquisition (RTDA) inputs during mock-up heart micro-surgery procedures. The trained network was used to estimate the tools poses from refined hand joint angles. Outputs of the network were surgical tool orientation and jaw angle acquired by an optical motion capture system. Results: Based on surgeon's feedback during mock micro-surgery, the developed wearable system with light-weight sensors for motion tracking did not interfere with the surgery and instrument handling. The wearable motion tracking system used 12 finger/thumb/wrist joint angle sensors to generate meaningful datasets representing inputs of the DNN network with new hand joint angles added as necessary based on comparing the estimated tool poses against measured tool pose. The DNN architecture was optimized for the highest estimation accuracy and the ability to determine the tool pose with the least mean squared error. This novel approach showed that the surgical instrument's pose, an essential requirement for teleoperation, can be accurately estimated from recorded surgeon's hand/finger movements with a mean squared error (M

关键词： feature extraction hand tracking machine learning minimally invasive surgery real-Time low-cost hand tracking Robot-Assisted surgery

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Robust Stabilizing Control for Oscillatory Base Manipulators by Implicit Lyapunov Method

Research Square

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Research Square 2021年

作者： Guo, Yufei Hou, Baolin Xu, Shengyue Mei, Ruilin Wang, Zhigang Huynh, Van Thanh Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education School of Machinery and Automation Wuhan University of Science and Technology Wuhan430081 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430081 China Shool of Mechanical Engineering Nanjing University of Science and Technology Nanjing210094 China Shool of Engineering Deakin University GeelongVIC3217 Australia

Oscillatory base manipulators (OBMs) are a kind of mechanical systems suffering from unexpected base oscillations. The oscillations affect tremendously system stability. Various control methods have been explored, but most of them require measurement or prediction of the oscillations. This study is concerned with a novel OBM–the autoloader, which are used in modern, autonomous main battle tanks. The base oscillation of the autoloader is hard to be obtained in practice. Furthermore, control synthesis for autoloaders is complicated with intrinsic payload uncertainty and actuator saturation. To address these issues, a novel robust control scheme is proposed in this work relying on the implicit Lyapunov method. Moreover, a novel two-Degree-of-Freedom manipulator operating on a vibrating base is constructed to realize the proposed control. To the best of the authors’ knowledge, this is the first study considering both control and hardware implementation for the OBM-like autoloaders. Experimental results demonstrate that, although without prior information of the base oscillation, the proposed controller exhibits good robustness against the base oscillation and payload uncertainty. © 2021, CC BY.

关键词： Manipulators

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