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Area-oriented coordinated trajectory planning of dual-arm space robot for capturing a tumbling target

Chinese Journal of Aeronautics 2019年第9期32卷 2151-2163页

作者： Wenfu XU Lei YAN Zhonghua HU Bin LIANG School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen 518055China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China Department of Automation Tsinghua UniversityBeijing 100084China

The growing amount of space debris poses a threat to operational spacecraft and the long-term sustainability of activities in outer space. According to the orbital mechanics, an uncontrolled space object will be tumbling, bringing great challenge to capture and remove it. In this paper, a dual-arm coordinated ‘‘Area-Oriented Capture'(AOC) method is proposed to capture a non-cooperative tumbling target. Firstly, the motion equation of the tumbling target is established, based on which, the dynamic properties are analyzed. Then, the ‘‘Area-Oriented Capture'concept is presented to deal with the problem of large pose(position and attitude) deviation and tumbling motion. An area rather than fixed points/devices is taken as the object to be tracked and captured. As long as the manipulators’ end-effectors move to a specified range of the objective areas(not fixed points on the target, but areas), the target satellite will be hugged by the two *** last, the proposed method and the traditional method(i.e. fixed-point oriented capture method)are compared and analyzed through simulation. The results show that the proposed method has larger pose tolerance and takes shorter time for capturing a tumbling target.

关键词： Area-oriented capture Dual-arm coordination Space debris removal Space robot Tumbling target capturing

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Conditional Generative Models for Simulation of EMG During Naturalistic Movements

arXiv

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arXiv 2022年

作者： Ma, Shihan Clarke, Alexander Kenneth Maksymenko, Kostiantyn Deslauriers-Gauthier, Samuel Sheng, Xinjun Zhu, Xiangyang Farina, Dario The Department of Bioengineering Imperial College London United Kingdom The State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai China The Meta Robotics Institute Shanghai Jiao Tong University Shanghai China Neurodec Sophia Antipolis France Inria Centre Université Côte d’Azur Nice France

Numerical models of electromyographic (EMG) signals have provided a huge contribution to our fundamental understanding of human neurophysiology and remain a central pillar of motor neuroscience and the development of human-machine interfaces. However, whilst modern biophysical simulations based on finite element methods are highly accurate, they are extremely computationally expensive and thus are generally limited to modelling static systems such as isometrically contracting limbs. As a solution to this problem, we propose a transfer learning approach, in which a conditional generative model is trained to mimic the output of an advanced numerical model. To this end, we present BioMime, a conditional generative neural network trained adversarially to generate motor unit activation potential waveforms under a wide variety of volume conductor parameters. We demonstrate the ability of such a model to predictively interpolate between a much smaller number of numerical model’s outputs with a high accuracy. Consequently, the computational load is dramatically reduced, which allows the rapid simulation of EMG signals during truly dynamic and naturalistic movements. Copyright © 2022, The Authors. All rights reserved.

关键词： Numerical models

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Redistributing Controller Orders to Increase Positioning Bandwidth in Nanopositioners

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IFAC-PapersOnLine 2021年第21期54卷 97-102页

作者： Adedayo K. Babarinde Linlin Li Jakub Kuncak LiMin Zhu Sumeet S. Aphale Artificial Intelligence Robotics and Mechatronic Systems Group School of Engineering University of Aberdeen Aberdeen AB24 3UE UK State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai 200240 China

Integer-order damping and tracking controllers are typically used in tandem to overcome resonance and hysteresis induced positioning errors in piezo-actuated nanopositioners. This paper takes a novel approach of strategically redistributing the controller orders to achieve significant positioning bandwidth improvement, without any significant increase in the design complexity. The Positive Position Feedback (PPF) controller combined with a suitably gained Integral tracking controller is used as a candidate to demonstrate the efficacy of the proposed technique. The resulting fractional-order PPF damping and Integral tracking controllers result in increasing the overall positioning bandwidth of the closed-loop system by 37%; and subsequent improvement in positioning accuracy while tracking high-frequency triangular trajectories.

关键词： Nanopositioners piezoelectric actuator positive position feedback tracking control fractional-order control

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17β-Trenbolone modulates anxiety-related synaptic plasticity by affecting the interaction between hippocampal TACR3 and systemic testosterone in male mice

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Environmental Research 2025年第Pt 1期279卷 121796页

作者： Zuo, Xiang Bai, Huijuan Qiu, Jinyu Li, Ruimin Kuang, Xiaochen Zhao, Yudi Tuo, Jingyi Zhao, Qili Zhao, Xin Feng, Xizeng College of Life Science State Key Laboratory of Medicinal Chemical Biology Key Laboratory of Bioactive Materials Ministry of Education Nankai University Tianjin300071 China Institute of Robotics & Automatic Information System College of Artificial Intelligence Nankai University Tianjin300071 China

Anxiety Disorder is a common neurological disorder for which ubiquitous environmental endocrine disruptors may be risk factors. 17β-trenbolone (17-TB) has been recognized as a potential environmental endocrine disruptor and its neurotoxic effects have attracted attention. Tachykinin receptor 3 (TACR3), a G protein-coupled receptor involved in pubertal anxiety, and its underlying neural mechanisms remain enigmatic. Therefore, this study investigated the possible relationship between 17-TB and TACR3, testosterone (T), and synaptic plasticity. Our results showed that adolescent male Balb/c mice developed significant anxiety-like behavior after four weeks of exposure to environmentally relevant concentrations of 17-TB (100 μg/kg/day). Transcriptomic RNA-Seq results showed that 17-TB affected abnormal synaptic transmission signals in the hippocampus. Electrophysiological results showed that 17-TB reduced the activity of hippocampal dentate gyrus (DG) neurons and led to the downregulation of hippocampal TACR3 and T levels. In addition, Western blot, immunohistochemistry, ELISA, and qRT-PCR showed that 17-TB exposure led to the downregulation of key hippocampal synaptic proteins PSD95, Gephyrin, and Syn, and induced a metabolic imbalance in glutamate (Glu)/GABA signaling, affecting dopamine signaling. Interestingly, testosterone supplementation (10 mg/kg/day) was effective in ameliorating the above phenomena and alleviating anxiety-like behaviors. These results suggest that 17-TB modulates anxiety-related synaptic plasticity by regulating hippocampal TACR3 and T interactions in vivo. In conclusion, our study contributes to understanding the neurobehavioral and potential mechanistic effects of environmental 17-TB exposure in mammals. It alerts the public to the health risks of chemicals to mammals and suggests new research directions and potential therapeutic targets. © 2025 Elsevier Inc.

关键词： Endocrinology

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XNORAM: An Efficient Computing-in-Memory Architecture for Binary Convolutional Neural Networks with Flexible Dataflow Mapping

XNORAM: An Efficient Computing-in-Memory Architecture for Bi...

引用

IEEE International Conference on Artificial Intelligence Circuits and systems (AICAS)

作者： Shiwei Liu Haozhe Zhu Chixiao Chen Lihua Zhang C.-J. Richard Shi State Key Laboratory of ASIC and System Shanghai Engineering Research Center for AI & Robotics Fudan University Shanghai

ISBN: (数字)9781728149226

ISBN: (纸本)9781728149233

In this paper, an energy-efficient computing-in-memory architecture for binary convolutional neural networks, called XNORAM, is proposed. The XNORAM employs 6T feature cells and 10T weight cells to form one XNORAM column. Multiplexed XNOR operations are embedded in each column. To address the data reuse in convolutional neural networks, flexible dataflow mapping is supported on XNORAM to minimize the external data access. To verify the architecture, we design a 4-KB XNORAM prototype in 65nm CMOS technology. It achieves a throughput of 18. 5GOPs at 100-MHz clock rate and 1.0-V power supply. XNOR-AlexNet is performed on the design achieving 39.86 TOPS/W and 4.63 GOPS/KB utilization with only 1.3% accuracy loss comparing to the original XNOR-Net result on GPUs.

关键词： Convolution Computer architecture Prototypes Topology Convolutional neural networks CMOS technology Throughput

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Design and Experiment of a Compact Cable-Driving Module for Reconfigurable Cable-Driven Parallel Robots

Research Square

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Research Square 2020年

作者： Yuan, Han An, Hao Zhang, Yongqing Xu, Wenfu Shenzhen518055 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150080 China

Cable-driven parallel robots (CDPRs) have the characteristics of reconfigurability, which endows CDPRs with flexible workspace, freely configurable degrees of freedom and various configurations, greatly expanding their range of applications. Modular design provides great convenience and feasibility for the realization of reconfiguration, which is a key issue of reconfiguration research. However, most existing CDPRs have problems of low modularity and low system integration, which brings inconvenience to the realization of reconfiguration. In this paper, a highly integrated and high precision cable-driving module is designed, which can accurately control the length and tension of the cable. In addition, experimental verification is performed. The single-module experiment shows that the module has good ability for cable length and cable tension control. The cable length control error is less than 0.2mm, and the cable tension control error is less than 0.8N. Furthermore, based on the proposed module, a CDPR with 8 cables and 6 degrees of freedom is constructed rapidly. The open-loop tracking error of the robot is measured by laser tracker. Results show that the tracking error is less than 4.5mm and the Root-Mean-Square-Error (RMSE) is 2.1mm. Besides, the compliance control experiment of the robot shows that the tracking error in impedance control mode is less than 2mm, and the RMSE is 0.95mm, and the drag force in teaching mode is less than 2.5N, which demonstrates good follow-up performance. The proposed compact cable-driving module with high precision could be useful for the design and rapid construction of reconfigurable CDPRs. © 2020, CC BY.

关键词： Cables

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Aeroengine remaining useful life prediction via integrating enhanced inverted transformer and spatiotemporal graph learning

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ISA Transactions 2025年

作者： Sun, Shilong Ding, Hao Zhao, Zida Zhou, Yu Wang, Dong Xu, Wenfu School of Robotics and Advanced Manufacturing College of Artificial Intelligence Harbin Institute of Technology Shenzhen China Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai200240 China

Accurate prediction of aeroengine Remaining Useful Life (RUL) is critical for ensuring flight safety, minimizing maintenance costs, and improving operational efficiency. This study proposes a novel model, the Fourier-Enhanced Inverted Transformer with Graph-Augmented Spatiotemporal Modeling (FIT-GSTM), to enhance RUL prediction performance. FIT-GSTM combines an inverted Transformer with a Spatiotemporal Graph Convolutional Network (STGCN) to effectively capture global spatiotemporal dependencies across multi-sensor data. To further enrich feature representation, the model incorporates Fast Fourier Transform (FFT) to extract frequency-domain information and fuses it with time-domain features, enhancing robustness to noise. Additionally, the integration of Memory Tokens and Reversible Instance Normalization (RevIN) strengthens the model's ability to retain long-term dependencies and adapt to heterogeneous data distributions. Experimental evaluations on the C-MAPSS dataset demonstrate that FIT-GSTM achieves superior RUL prediction accuracy and generalization compared to existing methods, highlighting its potential for real-world deployment in aeroengine health management. © 2025 ISA

关键词： Fast Fourier transforms

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An Efficient Planning and Control Framework for Quadrotors Based on Heuristic Search and Data-Driven Model Predictive Control

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IEEE Transactions on Industrial Electronics 2025年

作者： Wang, Sifei Wang, Yaonan Miao, Zhiqiang Wang, Xiangke He, Wei Wang, Hesheng Hunan University College of Electrical and Information Engineering Changsha410082 China National Engineering Research Center for Robot Visual Perception and Control Changsha410082 China National University of Defense Technology College of Intelligence Science and Technology Changsha410073 China Beijing Information Science and Technology University School of Automation Institute of Artificial Intelligence Beijing100083 China University of Science and Technology School of Intelligence Science and Technology Beijing100083 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

This article presents a framework for quadrotors that integrate planning and control, which employs a heuristic depth-first search (HDFS) with data-driven model predictive control (MPC). The proposed framework intends to enable multiquadrotor systems to traverse cluttered environments containing obstacles and disturbances. The heuristic function enables quadrotors to identify a secure route in a timely manner. The heuristic function setup employed by HDFS results in a reduction in the number of rasters accessed, particularly in scenarios that are not labyrinthine. This consequently leads to an enhancement in computational speed for multiquadrotor systems when compared to the A* algorithm. Furthermore, data-driven MPC enhances the nominal model of the quadrotor by modeling the disturbance while tracking the desired states. Consequently, data-driven MPC is capable of attaining superior tracking precision in a disturbance environment when compared to MPC without data-driven. The transformation from the path to the desired states of the quadrotor is achieved through the utilization of B-splines and differential flatness. Simulations and experiments substantiate the efficacy of the proposed approach. © 1982-2012 IEEE.

关键词： Predictive control systems

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A Spray Path Planning Algorithm based on 3D Point Cloud 3

A Spray Path Planning Algorithm based on 3D Point Cloud

引用

3rd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2019

作者： Tong, Ning Kong, Minxiu Xu, Shengrun Harbin Institute of Technology School of Mechatronics Engineering China State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9781728105130

Robotic spray path planning for complex surface has always been a challenging problem, especially when it comes to flexible manufacturing system. This paper presents a new method to plan the spray path based on the point cloud obtained by vision sensors. In order to select the direction of slice adaptively, a method based on principal component analysis (PCA) is adopted to calculate the dominant eigenvector of point cloud. The intersection algorithm is also discussed to obtain points for constructing spraying path. The normal vector calculation and sorting problem of slice points are also solved. The experimental results show that the proposed path planning method can automatically generate the spraying path according to the surface of spray target. This method can also be extended to other applications. © 2019 IEEE.

关键词： Principal component analysis

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Anomaly Detection of Marine Diesel Engine Valve system based on Mahalanobis Distance

Anomaly Detection of Marine Diesel Engine Valve System based...

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2020 Global Reliability and Prognostics and Health Management, PHM-Shanghai 2020

作者： Sun, Yue Xu, Aidong Wang, Kai Jia, Shuli Guo, Haifeng Han, Xiaojia Laboratory of Industrial Control Network and System State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Shenyang China Automation Engineering Department Shanghai Marine Diesel Engine Research Institute Shanghai China

ISBN: (纸本)9781728159454

Diesel engine is an important energy equipment. The valve system is the core component of diesel engine with high failure rate. It is of great significance to study the abnormal detection method of the diesel engine valve system and realize the failure warning before the failure occurs for avoiding the unexpected shutdown of the diesel engine. In this paper, an anomaly detection method of marine diesel engine valve system based on Mahalanobis distance (MD) is proposed. The failure mode of diesel engine system is analyzed. Three thermal parameters are selected as monitoring parameters for the failure mode of roller fragmentation. Fault features are extracted by MD method and the failure threshold is determined by Box-Cox transformation. Finally, the effectiveness of the proposed method is verified by the durability test of diesel engine. © 2020 IEEE.

关键词： Diesel engines

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