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Fast automatic docking control for electric tractors

Fundamental Research 2024年

作者： Li, Pengpeng Bai, Yu Li, Weihua Chen, Bowen You, Bindi Zhuang, Hongchao Wang, Jianfeng Gao, Haibo Deng, Zongquan School of Astronautics Harbin Institute of Technology Harbin 150001 China School of Automotive Engineering Harbin Institute of Technology (Weihai) Weihai 264201 China Yangtze River Delta HIT robot technology research institute Wuhu 241060 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China Tianjin University of Technology and Education Tianjin 300222 China

In this study, we investigate the automatic docking of an electric tractor with a semi-trailer in narrow and long-distance scenarios. We propose an automatic docking method based on a multi-sensor fusion high-precision positioning algorithm and a multi-strategy docking control algorithm. To solve the heading-angle error of the involved camera due to mechanical errors, a compensation value in the form of angle deviation is introduced. To alleviate the increase in the camera detection error with longitudinal distance, a piecewise coordinate compensation function is proposed. Repositioning is performed using light detection and ranging (Lidar) to improve the pose-perception accuracy to the millimeter level. To avoid the interference of point clouds on the relocation accuracy of Lidar, a search-and-location method that combines both small and large neighborhoods is proposed. To achieve the desired docking success rate, a multi-strategy-adjustment control algorithm is used to enable comprehensive adjustment, including approximate control of the maximum angle based on lateral deviation and fine proportional-integral-differential (PID) control based on lateral deviation and longitudinal distance, security check cycle and premature warning mechanism, and risk avoidance control. Finally, the reliability and stability of the design scheme are verified by conducting multiple experiments involving actual vehicles. © 2024

关键词： Automatic docking Electric tractor Fusion positioning Piecewise proportional-integral-differential

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A novel End-effector Finger Rehabilitation Robot (EFRR) for stroke patients

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Journal of Physics: Conference Series 2021年第5期1885卷

作者： Wang Hongbo Tian Yu Niu Baoshan Du Jiazheng Tian Junjie Parallel Robot and Mechatronic System Laboratory of Hebei Province Yanshan University Qinhuangdao 066004 China Academy for Engineering & Technology Fudan University Shanghai 200433 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150080 China

This paper proposes a prototype of a novel end-traction finger rehabilitation robot with flexion/extension and adduction/abduction functions. The degree of freedom (DoF) and finger joint torque of a single-finger module has been analysed, and the calculation and selection of the motor driving force are completed. Finally, the design details of the mechanism and the hardware system of the robot are illustrated. This device minimized the mechanical size to some extent by using only one motor for a single finger, which also reduces the cost and increases the possibility of industrial application prospects.

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Corrigendum to “Drill-soil penetration model and its application to lunar exploration” [Adv. Space Res. 70(11) (2022) 3436–3449]

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Advances in Space Research 2023年第8期71卷 3532-3532页

作者： Ye Tian Jiahang Zhang Weiwei Zhang Boyi Xu Zhangqing Duan School of Light Industry Harbin University of Commerce Harbin 150028 PR China The State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 PR China

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Bacteria Flagella-Mimicking Polymer Multilayer Magnetic Microrobots

SSRN

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SSRN 2024年

作者： Wu, Zhiguang Lu, Liang Bai, Shuang Shi, Jiaqi Zhang, Zhuotao Pan, Yunlu Wang, Wei Wu, Wenfeng Sun, Shoubin Li, Xu Hou, Gang Huang, Tianyun Jia, Yuxin Zuo, Kaiwen Granovsky, Alexander Wu, He Nikolai, Perov School of Medicine and Health Harbin Institute of Technology Harbin China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China The First Affiliated Hospital of Harbin Medical University Harbin China National Center for Respiratory Medicine State Key Laboratory of Respiratory Health and Multimorbidity National Clinical Research Center for Respiratory Diseases Institute of Respiratory Medicine Chinese Academy of Medical Sciences Department of Pulmonary and Critical Care Medicine Center of Respiratory Medicine China-Japan Friendship Hospital Beijing China College of Science Sichuan Agricultural University Chengdu China The Fourth Affiliated Hospital of Harbin Medical University Harbin China Department of Ophthalmology The Second Hospital Jilin University Changchun China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China Department of Mathematics Imperial College London United Kingdom Department of Computer Science University of Warwick Coventry United Kingdom Magnetism Department Faculty of Physics Lomonosov Moscow State University Moscow Russia Harbin Medical University China

Learning from natural bacteria flagellum, we demonstrate a magnetic polymer multilayer conical microrobot that bestow the controllable propulsion upon external rotating magnetic field with uniform intensity. The magnetic microrobots were constructed by template-assisted Layer-by-Layer technique technique and subsequent functionalization of magnetic particle onto the big opening of the microrobots. Geometric variables of the polymer microrobots, such as the diameter and wall thickness, can be controlled by selection of porous template and layers of assembly. The microrobots perform controllable propulsion through the manipulation of magnetic field. The comparative analysis of the movement behavior reveals that the deformation of microrobots may attributed to the propulsion upon rotating magnetic field, which is similar as that of natural bacteria. The influence of actuation frequencies and frequencies on the velocity of the microrobots is studied. Such use of polymer polymer multilayer tubular micro/nanoarchitectures results in significant savings in the processing costs and provides a simple and cost-effective fabrication route for the mass production of magnetic polymer microrobots. © 2024, The Authors. All rights reserved.

关键词： Bacteria

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Correction to: Fabrication of high-strength polyoxymethylene fibers by gel spinning

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Journal of Materials Science 2018年第18期53卷 13316-13316页

作者： Xudong Fang Tom Wyatt Jing Shi Donggang Yao School of Mechanical Engineering Xi’an Jiaotong University Xi’an China School of Materials Science and Engineering Georgia Institute of Technology Atlanta USA State Key Laboratory for Manufacturing Systems Engineering Xi’an China State Key Laboratory of Robotics and System (HIT) Harbin China

In the original article, the name of author Donggang Yao was misspelled. It is correct here.

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Joint learning of discriminative low-dimensional image representations based on dictionary learning and two-layer orthogonal projections

arXiv

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arXiv 2019年

作者： Wei, Xian Shen, Hao Li, Yuanxiang Tang, Xuan Jin, Bo Zhao, Lijun Murphey, Yi Lu Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences China Technical University of Munich Germany and fortiss GmbH Munich Germany Shanghai Key Lab for Trustworthy Computing School of Computer Science and Software Engineering East China Normal University China School of Aeronautics & Astronautics Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150006 China Department of Electrical and Computer Engineering University of Michigan-Dearborn DearbornMI48128 United States

This work investigates the problem of efficiently learning discriminative low-dimensional representations of multi-class large-scale image objects. We propose a generic deep learning approach by taking advantages of Convolutional Neural Networks (CNN), sparse dictionary learning, and orthogonal projections. CNN is not only powerful on feature extraction, but also robust to spatial variance and changes. Sparse dictionary learning is well known for disentangling nonlinear underlying discriminative factors in data. The orthogonal projection is a notable efficient tool to project multi-class data onto low dimensional discriminative subspace. The proposed procedure can be summarized as follows. At first, a CNN is employed to extract high-dimensional (HD) preliminary convolutional features. Secondly, to avoid the high computational cost of direct sparse coding on HD CNN features, we present to learn sparse representation (SR) in an orthogonal projected space over a task-driven sparsifying dictionary. We then exploit the discriminative projection on SR. The whole learning process is treated as a joint optimization problem of trace quotient maximization, which involves the CNN parameters, the orthogonal projection on CNN features, the dictionary and the discriminative projection on sparse codes. The related cost function is well defined on product manifold of the Stiefel manifold, the Oblique manifold, and the Grassmann manifold. It is optimized via a geometrical stochastic gradient descent algorithm. Finally, the quality of dictionary and projections learned by the proposed approach is further investigated in terms of image classification. The experimental results show that the approach can achieve a strongly competitive performance with state-of-the-art image classification methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Convolution

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Scientific Exploration of Challenging Planetary Analog Environments with a Team of Legged Robots

arXiv

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arXiv 2023年

作者： Arm, Philip Waibel, Gabriel Preisig, Jan Tuna, Turcan Zhou, Ruyi Bickel, Valentin Ligeza, Gabriela Miki, Takahiro Kehl, Florian Kolvenbach, Hendrik Hutter, Marco Robotic Systems Lab ETH Zurich Zurich Switzerland State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Laboratory of Hydraulics Hydrology and Glaciology ETH Zurich Zurich Switzerland Center for Space and Habitability University of Bern Bern Switzerland Department of Environmental Sciences University of Basel Basel Switzerland University of Zurich Dübendorf Switzerland Center for Theoretical Astrophysics and Cosmology University of Zurich Zurich Switzerland Institute of Medical Engineering Space Biology Group Lucerne University of Applied Sciences and Art Hergiswil Switzerland

The interest in exploring planetary bodies for scientific investigation and in-situ resource utilization is ever-rising. Yet, many sites of interest are inaccessible to state-of-the-art planetary exploration robots because of the robots’ inability to traverse steep slopes, unstructured terrain, and loose soil. Additionally, current single-robot approaches only allow a limited exploration speed and a single set of skills. Here, we present a team of legged robots with complementary skills for exploration missions in challenging planetary analog environments. We equipped the robots with an efficient locomotion controller, a mapping pipeline for online and post-mission visualization, instance segmentation to highlight scientific targets, and scientific instruments for remote and in-situ investigation. Furthermore, we integrated a robotic arm on one of the robots to enable high-precision measurements. Legged robots can swiftly navigate representative terrains, such as granular slopes beyond 25 degrees, loose soil, and unstructured terrain, highlighting their advantages compared to wheeled rover systems. We successfully verified the approach in analog deployments at the BeyondGravity ExoMars rover testbed, in a quarry in Switzerland, and at the Space Resources Challenge in Luxembourg. Our results show that a team of legged robots with advanced locomotion, perception, and measurement skills, as well as task-level autonomy, can conduct successful, effective missions in a short time. Our approach enables the scientific exploration of planetary target sites that are currently out of human and robotic reach. Copyright © 2023, The Authors. All rights reserved.

关键词： Robots

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Nanorobots: Magnetically Propelled Fish-Like Nanoswimmers (Small 44/2016)

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Small 2016年第44期12卷

作者： Tianlong Li Jinxing Li Hongtao Zhang Xiaocong Chang Wenping Song Yanan Hu Guangbin Shao Elodie Sandraz Guangyu Zhang Longqiu Li Joseph Wang State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang 150001 China Department of Nanoengineering University of California San Diego La Jolla CA 92093 USA

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Mechanics of soft-body rolling motion without external torque

arXiv

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arXiv 2024年

作者： Liang, Xudong Ding, Yimiao Yuan, Zihao Jiang, Junqi Xie, Zongling Fei, Peng Sun, Yixuan Gu, Guoying Zhong, Zheng Chen, Feifei Si, Guangwei Gong, Zhefeng School of Science Harbin Institute of Technology Shenzhen518055 China Department of Neurology The Fourth Hospital and School of Brain Science and Brain Medicine Zhejiang University School of Medicine Hangzhou310058 China Liangzhu Laboratory MOE Frontier Science Center for Brain Science and Brain-Machine Integration State Key Laboratory of Brain-Machine Intelligence Zhejiang University 1369 West Wenyi Road Hangzhou311121 China NHC and CAMS Key Laboratory of Medical Neurobiology Zhejiang University Hangzhou310058 China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai200240 China Robotics Institute School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Brain and Cognitive Science Institute of Biophysics Chinese Academy of Sciences 15 Datun Road Beijing100101 China University of Chinese Academy of Sciences 19A Yuquan Road Beijing100049 China Huazhong University of Science and Technology Optical and Electronic Information Wuhan430074 China Zhejiang Lab. Hangzhou311121 China

The Drosophila larva, a soft-body animal, can bend its body and roll efficiently to escape danger. However, contrary to common belief, this rolling motion is not driven by the imbalance of gravity and ground reaction forces. Through functional imaging and ablation experiments, we demonstrate that the sequential actuation of axial muscles within an appropriate range of angles is critical for generating rolling. We model the interplay between muscle contraction, hydrostatic skeleton deformation, and body-environment interactions, and systematically explain how sequential muscle actuation generates the rolling motion. Additionally, we constructed a pneumatic soft robot to mimic the larval rolling strategy, successfully validating our model. This mechanics model of soft-body rolling motion not only advances the study of related neural circuits, but also holds potential for applications in soft robotics. © 2024, CC BY.

关键词： Pneumatics

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Long-term Dependency for 3D Reconstruction of Freehand Ultrasound Without External Tracker

arXiv

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arXiv 2023年

作者： Li, Qi Shen, Ziyi Li, Qian Barratt, Dean C. Dowrick, Thomas Clarkson, Matthew J. Vercauteren, Tom Hu, Yipeng The UCL Centre for Medical Image Computing The Wellcome/EPSRC Centre for Interventional and Surgical Sciences Department of Medical Physics and Biomedical Engineering University College London LondonWC1E 6BT United Kingdom State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China School of Biomedical Engineering & Imaging Sciences King’s College London LondonWC2R 2LS United Kingdom

Objective: Reconstructing freehand ultrasound in 3D without any external tracker has been a longstanding challenge in ultrasound-assisted procedures. We aim to define new ways of parameterising long-term dependencies, and evaluate the performance. Methods: First, long-term dependency is encoded by transformation positions within a frame sequence. This is achieved by combining a sequence model with a multi-transformation prediction. Second, two dependency factors are proposed, anatomical image content and scanning protocol, for contributing towards accurate reconstruction. Each factor is quantified experimentally by reducing respective training variances. Results: 1) The added long-term dependency up to 400 frames at 20 frames per second (fps) indeed improved reconstruction, with an up to 82.4% lowered accumulated error, compared with the baseline performance. The improvement was found to be dependent on sequence length, transformation interval and scanning protocol and, unexpectedly, not on the use of recurrent networks with long-short term modules;2) Decreasing either anatomical or protocol variance in training led to poorer reconstruction accuracy. Interestingly, greater performance was gained from representative protocol patterns, than from representative anatomical features. Conclusion: The proposed algorithm uses hyperparameter tuning to effectively utilise long-term dependency. The proposed dependency factors are of practical significance in collecting diverse training data, regulating scanning protocols and developing efficient networks. Significance: The proposed new methodology with publicly available volunteer data and code1 for parametersing the long-term dependency, experimentally shown to be valid sources of performance improvement, which could potentially lead to better model development and practical optimisation of the reconstruction application. © 2023, CC BY.

关键词： Ultrasonics

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