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arXiv 2022年

作者： Ying, Xiong Leng, Si-Yang Ma, Huan-Fei Nie, Qing Lai, Ying-Cheng Lin, Wei School of Mathematical Sciences SCMS SCAM Fudan University Shanghai200433 China Research Institute for Intelligent Complex Systems CCSB LCNBI Fudan University Shanghai200433 China State Key Laboratory of Medical Neurobiology MOE Frontiers Center for Brain Science Institutes of Brain Science Fudan University Shanghai200032 China Institute of AI and Robotics Academy for Engineering and Technology Fudan University Shanghai200433 China School of Mathematical Sciences Soochow University Suzhou215006 China Department of Mathematics Department of Developmental and Cell Biology NSF-Simons Center for Multiscale Cell Fate Research University of California IrvineCA92697-3875 United States School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287-5706 United States Shanghai Artificial Intelligence Laboratory Shanghai200232 China

Data based detection and quantification of causation in complex, nonlinear dynamical systems is of paramount importance to science, engineering and beyond. Inspired by the widely used methodology in recent years, the cross-map-based techniques, we develop a general framework to advance towards a comprehensive understanding of dynamical causal mechanisms, which is consistent with the natural interpretation of causality. In particular, instead of measuring the smoothness of the cross map as conventionally implemented, we define causation through measuring the scaling law for the continuity of the investigated dynamical system directly. The uncovered scaling law enables accurate, reliable, and efficient detection of causation and assessment of its strength in general complex dynamical systems, outperforming those existing representative methods. The continuity scaling based framework is rigorously established and demonstrated using datasets from model complex systems and the real world. Copyright © 2022, The Authors. All rights reserved.

关键词： Dynamical 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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Probabilistic learning vector quantization on manifold of symmetric positive definite matrices

arXiv

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arXiv 2021年

作者： Sonna, Fengzhen Tang Feng, Haifeng Tino, Peter Si, Bailu Ji, Daxiong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China School of computer Science University of Birmingham BirminghamB15 2TT United Kingdom School of Systems Science Beijing Normal University Beijing100875 China Institute of Marine Electronics and Intelligent Systems Ocean College Zhejiang University Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Engineering Research Center of Oceanic Sensing Technology and Equipment Ministry of Education Zhoushan316021 China

In this paper, we develop a new classification method for manifold-valued data in the framework of probabilistic learning vector quantization. In many classification scenarios, the data can be naturally represented by symmetric positive definite matrices, which are inherently points that live on a curved Riemannian manifold. Due to the non-Euclidean geometry of Riemannian manifolds, traditional Euclidean machine learning algorithms yield poor results on such data. In this paper, we generalize the probabilistic learning vector quantization algorithm for data points living on the manifold of symmetric positive definite matrices equipped with Riemannian natural metric (affine-invariant metric). By exploiting the induced Riemannian distance, we derive the probabilistic learning Riemannian space quantization algorithm, obtaining the learning rule through Riemannian gradient descent. Empirical investigations on synthetic data, image data, and motor imagery EEG data demonstrate the superior performance of the proposed method. © 2021, CC BY-NC-SA.

关键词： Learning algorithms

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Entropy-Modulated Short-Chain Cathode for Low-Temperature All-Solid-state Li−S Batteries

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Angewandte Chemie 2024年第1期137卷

作者： Wei Zhao Yan Zhang Qingsong Liu Yajie Song Xu Li Liping Ren Geping Yin Shuaifeng Lou Jiajun Wang MOE Engineering Research Center for Electrochemical Energy Storage and Carbon Neutrality in Cold Regions School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin 150001 China MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin 150001 China These authors contributed equally. State Key Laboratory of Robotics and Systems (HIT) Harbin Institute of Technology Harbin 150001 China Suzhou Research Institute of HIT Suzhou 215104 P. R. China

All-solid-state Li−S batteries (ASSLSBs) due to high theoretical energy density and exceptional safety are highly desirable for electric aircraft. However, as the flight altitude rises, the low-temperature performance is hampered by inadequate practical capacity. Here, we discover that low-temperature sulfur utilization is constrained by the multi-step endothermic conversion reaction. By introducing multi-chalcogen to modulate the local entropy, a short-chain molecule cathode is designed to shorten the reduction pathways and enhance low-temperature discharge capacity. Furthermore, the mismatched lithiation lattice of the short-chain cathode reduces the decomposition energy barriers, thus enhancing low-temperature charge/discharge reversibility. The designed short-chain cathode exhibits high cathode utilization (99.4 %) and cycling stability (400 cycles, 92.2 % retention) at room temperature, as well as delivers excellent discharge capacity (579.6 mAh g −1 , −40 °C) and cycling performance (100 cycles, 98.4 % retention, 394.9 Wh kg − 1electrode, −20 °C) at low temperature. This study presents new opportunities to stimulate the development of low-temperature ASSLSBs.

关键词： All-solid-state Li−S batteries low temperature reaction kinetic short-chain molecule high cathode utilization

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Haptic display for virtual reality: progress and challenges

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Virtual Reality & Intelligent Hardware 2019年第2期1卷 136-162页

作者： Dangxiao WANG Yuan GUO Shiyi LIU Yuru ZHANG Weiliang XU Jing XIAO State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100083China Beijing Advanced Innovation Center for Biomedical Engineering Beihang UniversityBeijing 100083China Peng Cheng Laboratory Shenzhen 518055China Department of Mechanical Engineering University of AucklandAuckland 1142New Zealand School of Computer Science and the Robotics Engineering Program Worcester Polytechnic InstituteWorcesterMA 01609-2280USA

Immersion, interaction, and imagination are three features of virtual reality (VR). Existing VR systems possess fairly realistic visual and auditory feedbacks, and however, are poor with haptic feedback, by means of which human can perceive the physical world via abundant haptic properties. Haptic display is an interface aiming to enable bilateral signal communications between human and computer, and thus to greatly enhance the immersion and interaction of VR systems. This paper surveys the paradigm shift of haptic display occurred in the past 30 years, which is classified into three stages, including desktop haptics, surface haptics, and wearable haptics. The driving forces, key technologies and typical applications in each stage are critically reviewed. Toward the future high-fidelity VR interaction, research challenges are highlighted concerning handheld haptic device, multimodal haptic device, and high fidelity haptic rendering. In the end, the importance of understanding human haptic perception for designing effective haptic devices is addressed.

关键词： Haptic display Virtual reality Desktop haptics Surface haptics Wearable haptics Multimodal haptics

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A 350 C piezoresistive n-type 4H-SiC pressure sensor for hydraulic and pneumatic pressure tests

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Journal of Micromechanics and Microengineering 2020年第5期30卷

作者： Fang, Xudong Wu, Chen Zhao, Yulong Jiang, Zhuangde Rong, Weibing Feng, Zhihong Lv, Yuanjie State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies Collaborative Innovation Center of Suzhou Nano Science and Technology Xi'an Jiaotong University Xi'an710049 China School of Mechanical Engineering Xi'an Jiaotong University Xi'an710049 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150080 China National Key Laboratory of Application Specific Integrated Circuit Hebei Semiconductor Research Institute Shijiazhuang050051 China

It has been a challenge to develop pressure sensors that can work in harsh environments. In this work, a piezoresistive n-type 4H-SiC pressure sensor is demonstrated, capable of working at 350 C under hydraulic and pneumatic pressure. The pressure measuring range of this sensor is 7 MPa and the chip dimension is 2.5 mm 2.5 mm 0.23 mm. A reliable Ti/TaSi2/Pt metal ohmic contact is used in the sensor and experimental results show that the metal combination can withstand a wide temperature range of 30 C-350 C. In order to avoid thermal stress induced by the mismatch of thermal expansion coefficients of different packaging materials when increasing temperature, a double-layer bonding scheme of cement glue and epoxy is proposed. The inner layer of the chip and the kovar alloy base are directly bonded with the epoxy, while the outer layer is wrapped with the high-temperature cement glue. Experiments confirm that this method can achieve reliable packaging with temperatures up to 350 C for 5 h. Based on the above key technologies, the sensitivity of this sensor can reach 13.2 mV V-1 kPa-1 and the test data exhibit high linearity and repeatability. Static tests prove that the sensor has good media compatibility which can operate under a hydraulic pressure load at 220 C and a barometric pressure load under 350 C. The sensor in this work can provide a reference for pressure measurements at high temperature and in complex media environments. © 2020 IOP Publishing Ltd.

关键词： Pressure sensors

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A Two-Stage Learning Framework for Driver Lane Change Intention Inference

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IFAC-PapersOnLine 2020年第5期53卷 638-643页

作者： Yang Xing Bin Tian Chen Lv Dongpu Cao School of Mechanical and Aerospace Engineering Nanyang Technological University 639798 Singapore State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences and School of Artificial Intelligence University of Chinese Academy of Sciences Beijing 100190 China Department of Mechanical and Mechatronics Engineering University of Waterloo ON N2L3G1 Canada

With the rapid development of intelligent vehicles, human drivers are sharing the control authority with the automation functionalities. The mutual understanding between the intelligent vehicle and the human driver is the key to the efficient multi-agent teaming and the collaborative driving system. In this study, a two-stage learning framework for spatial-temporal driver lane change intention inference is developed. The two-stage learning framework contains two separate parts. First, an operational level driving behavior recognition system based on the deep convolutional neural network (CNN) is developed to recognize the driver behaviors, including mirror checking and normal driving. Then, based on the driver behavior features from the CNN, the sequential feature vector will be used for the construction of driver intention inference model based recurrent neural networks (RNN) and long short-term memory (LSTM). The proposed model achieved a state-of-the-art result on the driver lane change intention inference task. Based on the naturalistic driving dataset, the model achieved over 91% accuracy for lane change and lane-keeping intention prediction. The two-stage learning framework can significantly increase the model flexibility and accuracy, which makes it easier to be implemented and updated in intelligent vehicles.

关键词： Driver Behavior Driver Model Deep Learning LSTM Intelligent Vehicle

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Identification of muscle morphology with noncontact capacitive sensing: Preliminary study

Identification of muscle morphology with noncontact capaciti...

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Enhao Zheng Jiacheng Wan Dongfang Xu Qining Wang Hong Qiao The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Information Engineering China university of geosciences (Beijing) Beijing China The Robotics Research Group College of Engineering Peking University Beijing China

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Human-machine interface with muscle signals serves as an important role in the field of wearable robotics. To compensate for the limitations of the existing surface Electromyography (sEMG) based technologies, we previously proposed a noncontact capacitive sensing approach that could record the limb shape changes. The sensing approach frees the human skin from contacting to the metal electrodes, thus enabling the measurement of muscle signals by dressing the sensing front-ends outside of the clothes. We validated the capacitive sensing in human motion intent recognition tasks with the wearable robots and produced comparable results to existing studies. However, the biological significance of the capacitance signals is still unrevealed, which is an indispensable issue for robot intuitive control. In this study, we address the problems of identifying the relationships between the muscle morphological parameters and the capacitance signals. We constructed a measurement system that recorded the noncontact capacitive sensing signals and the muscle ultrasound (US) images simultaneously. With the designed device, five subjects were employed and the US images from the gastrocnemius muscle (GM) and the tibialis anterior (TA) muscle during level walking were sampled. We fitted the calculated muscle morphological parameters (the pinnation angles and the muscle fascicle length) and the capacitance signals of the same gait phases. The results demonstrated that at least one-channel capacitance signal strongly correlated to the muscle morphological parameters (R 2 > 0.5, quadratic regression). The average R 2 s of the most correlated channels were up to 0.86 for pinnation angles and 0.83 for the muscle fascicle length changes. The interesting findings in this preliminary study suggest the biological physical significance of the capacitance signals during human locomotion. Future efforts are worth being paid in this new research direction for more promising results.

关键词： Muscles Robot sensing systems Capacitance Legged locomotion Electrodes Ultrasonic variables measurement

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Design Validation and Collision Studies of A Compliant Magnetorheological Fluid Actuator

Design Validation and Collision Studies of A Compliant Magne...

引用

IEEE International Conference on Human-Machine systems

作者： Guangzeng Chen Jie Pengyu Tongyi Shang Yunjiang Lou T.T. Wong Li Chen Jian Liu State Key Laboratory of Robotics and System School of Mechatronics Engineering and Automation Harbin Institute of Technology (Shenzhen) Shenzhen China. Shenzhen Institutes of Advanced Technology Shenzhen University Town Shenzhen China Emergency Department Chinese PLA General Hospital Department of Biomedical Engineering Shandong University Jinan China

ISBN: (数字)9781728158716

ISBN: (纸本)9781728158723

Robots are integrating into human society and become an important part. The robots and human must be considered as a whole system and the robots should be intelligent both in digital and physical like human to cooperate and interact with human non-physically or physically. For improving the physical intelligence of the robot, a magnetorheological fluid actuator (MRA) is proposed and studied in this paper. A collision model and a speed peak force planning method are proposed and some experiments are conducted. It shows that the collision peak force of the MRA with external objects can be easily controlled to different levels by controlling the compliance of the MRA for safe physical interaction with human or some striking works like hammering a nail.

关键词： Torque Robots Actuators Force Collision avoidance Rotors Couplings

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Dynamic Balance and Trajectory Tracking Control of Quadruped Robots Based on Virtual Model Control

Dynamic Balance and Trajectory Tracking Control of Quadruped...

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第三十九届中国控制会议

作者： Guangrong Chen Bowen Hou Sheng Guo Junzheng Wang Robotics Research Center Beijing Jiaotong University Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

As for a motion control framework of robots, virtual model control（VMC） can use virtual components to create virtual forces/torques. Actually, the virtual forces/torques are generated by joint actuators when the virtual components interact between robots and environments. In this paper, a virtual model control is proposed to do the dynamic balance control of quadruped robots in trot gait. In each leg, virtual model control includes swing phase control of robots and stance phase counterparts. In whole body, based on the forces/torques distribution method between two stance legs, virtual model control is mainly about the attitude control containing roll, pitch and yaw. Then, an intuitive approach of velocity control is employed for the locomotion of quadruped robots. Based on the velocity planning and control, a trajectory tracking control approach is investigated by considering four factors: terrain complexity index, curvature radius of given trajectory, distance to terminal, and maximum velocity of quadruped robots. Finally, the effectiveness of proposed controllers is validated by co-simulations.

关键词： Virtual model control Dynamic balance control Trajectory tracking control Quadruped robots

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