检索结果-内蒙古大学图书馆

arXiv 2020年

作者： Qiao, Zhijian Hu, Hanjiang Shi, Weiang Chen, Siyuan Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Mechanical Engineering Carnegie Mellon University United States Department of Computer Science and Technology University of Cambridge United Kingdom

In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic daytime and weather variance. However, it is time-consuming and effort-costly to obtain high-quality point cloud data for place recognition model training and ground truth for registration in the real world. To this end, a novel registration-aided 3D domain adaptation network for point cloud based place recognition is proposed. A structure-aware registration network is introduced to help to learn features with geometric information and a 6-DoFs pose between two point clouds with partial overlap can be estimated. The model is trained through a synthetic virtual LiDAR dataset through GTA-V with diverse weather and daytime conditions and domain adaptation is implemented to the real-world domain by aligning the global features. Our results outperform state-of-the-art 3D place recognition baselines or achieve comparable on the real-world Oxford RobotCar dataset with the visualization of registration on the virtual dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

来源：评论

学校读者我要写书评

暂无评论

The Use of Various Neurostimulators in Therapy of Neurodegenerative Disorders – A Survey

The Use of Various Neurostimulators in Therapy of Neurodegen...

引用

Progress in Applied Electrical engineering (PAEE)

作者： Aleksandra Kawala-Sterniuk Agata Gajos Mateusz Pawłowski Witold Libionka Władysław Piotr Duch Bartosz Pańczyszak Monika Stomal-Słowińska Michał Podpora Waldemar Bauer Adam Sudoł Mariusz Pelc Jarosław Zygarlicki Piotr Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Neurosurgery "Vital Medic" Hospital Kluczbork Poland Department of Extrapyramidal Diseases Medical University of Łódź Łódź Poland Faculty of Health Sciences Wroclaw Medical University Wrocław Poland Department of Automatic Control and Robotics AGH University of Science and Technology Kraków Poland Faculty of Natural Sciences and Technology University of Opole Opole Poland School Of Computing and Mathematical Sciences University of Greenwich London United Kindgom Center for Technology Transfer Opole University of Technology Opole Poland

ISBN: (数字)9781665455152

ISBN: (纸本)9781665455169

The use of neurostimulators in the treatment and therapy of neurodegenerative diseases is an alternative to pharmacological treatment. Unfortunately, most of these disorders are incurable, however, the use of neurostimulators can delay the onset of symptoms, the course of the disease and significantly improve the quality of life. Treatment with the use of neurostimulators also allows you to avoid side effects which usually accompany pharmacotherapy, or in order to replace it when prescribed medication is not working properly or not working at all. This paper focuses mainly on vagus nerve and deep brain stimulation.

关键词： Electrical engineering Deep brain stimulation Medical treatment Delays Diseases

来源：评论

学校读者我要写书评

暂无评论

Design of a Novel Autonomous Docking System With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

引用

IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multi-model least squares-based recomputation framework for large data analysis

arXiv

引用

arXiv 2021年

作者： Zhang, Wandong Wu, Q.M. Jonathan Yang, Yimin Zhao, W.G. Will Wang, TianLei Zhang, Hui Department of Electrical and Computer Engineering University of Windsor Windsor Canada Department of Computer Science Lakehead University Thunder Bay Canada Vector Institute for Artificial Intelligence Toronto Canada Faculty of Business Administration Lakehead University Canada Artificial Intelligence Group CEGEP de Ste Foy Canada Institute of Information and Control Hangzhou Dianzi University Hangzhou China School of Robotics Hunan University Changsha China

Most multilayer least squares (LS)-based neural networks, such as deep random vector functional link (RVFL), are structured with two separate stages: unsupervised feature encoding and supervised pattern classification. Once the unsupervised learning is finished, the latent encoding would be fixed without supervised fine-tuning. However, in complex tasks such as handling the ImageNet dataset, there are often many more clues that can be directly encoded, while the unsupervised learning, by definition, cannot know exactly what is useful for a certain task. There is a need to retrain the latent space representations in the supervised classification stage to learn some clues that unsupervised learning has not yet learned. In particular, the error matrix from the output layer is pulled back to each hidden layer, and the parameters of the hidden layer are recalculated with Moore-Penrose (MP) inverse for more generalized representations. In this paper, a recomputation-based multilayer network using MP inverse (RML-MP) is developed. A sparse RML-MP (SRML-MP) model to boost the performance of RML-MP is then proposed. The experimental results with varying training samples (from 3 K to 1.8 M) show that the proposed models provide better generalization performance than most representation learning algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal encoding

来源：评论

学校读者我要写书评

暂无评论

Trends and perspectives in proportional pneumatics

引用

IOP Conference Series: Materials Science and engineering 2020年第1期997卷

作者： M Avram A I Sgârciu C Bucşan Mechanical Engineering Mechatronics and Robotics Department POLITEHNICA University of Bucharest Bucharest Romania Automatic Control and Informatics Department POLITEHNICA University of Bucharest Bucharest Romania

Trends and perspective directions in the field of pneumatic equipment and systems are first identified in the paper. Special attention is given to identifying the equipment and systems that can be adapted to the requirements imposed by a new industrial revolution - Industry 4.0. Pneumatics will continue to be an important domain and the paper presents arguments for that. The current stage of proportional pneumatics is presented and a comparison between analog and digital proportional pneumatics is made. In the final part of the paper an experimental model of a distributor controlled with modulated pulses is presented. The distributor is integrated in a system that controls the pressure in a reference volume.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Anchor-based spatio-temporal attention 3D convolutional networks for dynamic 3D point cloud sequences

arXiv

引用

arXiv 2020年

作者： Wang, Guangming Chen, Muyao Liu, Hanwen Yang, Yehui Liu, Zhe Wang, Hesheng The Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China The Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science and Technology University of Cambridge

With the rapid development of measurwement technology, LiDAR and depth cameras are widely used in the perception of the 3D environment. Recent learning based methods for robot perception most focus on the image or video, but deep learning methods for dynamic 3D point cloud sequences are underexplored. Therefore, developing efficient and accurate perception method compatible with these advanced instruments is pivotal to autonomous driving and service robots. An Anchor-based Spatio-Temporal Attention 3D Convolution operation (ASTA3DConv) is proposed in this paper to process dynamic 3D point cloud sequences. The proposed convolution operation builds a regular receptive field around each point by setting several virtual anchors around each point. The features of neighborhood points are firstly aggregated to each anchor based on the spatio-temporal attention mechanism. Then, anchor-based 3D convolution is adopted to aggregate these anchors' features to the core points. The proposed method makes better use of the structured information within the local region and learns spatio-temporal embedding features from dynamic 3D point cloud sequences. Anchor-based Spatio-Temporal Attention 3D Convolutional Neural Networks (ASTA3DCNNs) are built for classification and segmentation tasks based on the proposed ASTA3DConv and evaluated on action recognition and semantic segmentation tasks. The experiments and ablation studies on MSRAction3D and Synthia datasets demonstrate the superior performance and effectiveness of our method for dynamic 3D point cloud sequences. Our method achieves the state-of-the-art performance among the methods with dynamic 3D point cloud sequences as input on MSRAction3D and Synthia datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Visual-Inertial and Leg Odometry Fusion for Dynamic Locomotion

Visual-Inertial and Leg Odometry Fusion for Dynamic Locomoti...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Victor Dhédin Haolong Li Shahram Khorshidi Lukas Mack Adithya Kumar Chinnakkonda Ravi Avadesh Meduri Paarth Shah Felix Grimminger Ludovic Righetti Majid Khadiv Joerg Stueckler Embodied Vision Group Max Planck Institute for Intelligent Systems Tuebingen Germany Movement Generation and Control Group Max Planck Institute for Intelligent Systems Tuebingen Germany Tandon School of Engineering New York University New York USA Oxford Robotics Institute University of Oxford England Autonomous Motion Department Max Planck Institute for Intelligent Systems Tuebingen Germany

Implementing dynamic locomotion behaviors on legged robots requires a high-quality state estimation module. Especially when the motion includes flight phases, state-of-the-art approaches fail to produce reliable estimation of the robot posture, in particular base height. In this paper, we propose a novel approach for combining visual-inertial odometry (VIO) with leg odometry in an extended Kalman filter (EKF) based state estimator. The VIO module uses a stereo camera and IMU to yield low-drift 3D position and yaw orientation and drift-free pitch and roll orientation of the robot base link in the inertial frame. However, these values have a considerable amount of latency due to image processing and optimization, while the rate of update is quite low which is not suitable for low-level control. To reduce the latency, we predict the VIO state estimate at the rate of the IMU measurements of the VIO sensor. The EKF module uses the base pose and linear velocity predicted by VIO, fuses them further with a second high-rate IMU and leg odometry measurements, and produces robot state estimates with a high frequency and small latency suitable for control. We integrate this lightweight estimation framework with a nonlinear model predictive controller and show successful implementation of a set of agile locomotion behaviors, including trotting and jumping at varying horizontal speeds, on a torque-controlled quadruped robot.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Simultaneous state and parameter estimation: The role of sensitivity analysis

arXiv

引用

arXiv 2020年

作者： Liu, Jianbang Gnanasekar, Aristarchus Zhang, Yi Bo, Song Liu, Jinfeng Hu, Jingtao Zou, Tao Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institute for Robotics & Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Chemical & Materials Engineering University of Alberta EdmontonABT6G 1H9 Canada Key Laboratory of Energy Thermal Conversion & Control Southeast University Nanjing210096 China School of Mechanical and Electrical Engineering Guangzhou University Guangzhou510006 China

State and parameter estimation is essential for process monitoring and control. Observability plays an important role in both state and parameter estimation. In simultaneous state and parameter estimation, the parameters are often augmented as extra states of the original system. When the augmented system is observable, various existing state estimation approaches may be used to estimate the states and parameters simultaneously. However, when the augmented system is not observable, how we should proceed to maximally extract the information contained in the measured outputs is not clear. This paper concerns about simultaneous state and parameter estimation when the augmented system is not fully observable. Specifically, we first show how sensitivity analysis is related to observability of a dynamical system, and then illustrate how it may be used to select variables for simultaneous estimation. We also propose a moving horizon state estimation (MHE) design that can use the variable selection results in a natural way. Extensive simulations are carried out to show the efficiency of the proposed approach. Copyright © 2020, The Authors. All rights reserved.

关键词： Sensitivity analysis

来源：评论

学校读者我要写书评

暂无评论

Urban Digital Twins for Intelligent Road Inspection

Urban Digital Twins for Intelligent Road Inspection

引用

IEEE International Conference on Big Data

作者： Rui Fan Yikang Zhang Sicen Guo Jiahang Li Yi Feng Shuai Su Yanting Zhang Wenshuo Wang Yu Jiang Mohammud Junaid Bocus Xingyi Zhu Qijun Chen the Department of Control Science & Engineering Frontiers Science Center for Intelligent Autonomous Systems and State Key Laboratory of Intelligent Autonomous Systems Robotics & Artificial Intelligence Laboratory (RAIL) Tongji University Shanghai P. R. China Department of Computer Science & Technology Donghua University Shanghai P. R. China Department of Civil Engineering McGill University Montreal Canada CTO office at ClearMotion Billerica MA USA Department of Electrical & Electronic Engineering the University of Bristol BS8 1UB U.K Key Laboratory of Road and Traffic Engineering of Ministry of Education Tongji University Shanghai P. R. China

ISBN: (纸本)9781665480468

Urban digital twin (UDT) technologies offer new opportunities for intelligent road inspection (IRI). This paper first reviews the state-of-the-art algorithms used in the two key components of UDT-based IRI systems: (1) multi-temporal, multi-dimension, multi-score, and heterogeneous road data acquisition, and (2) road distress detection. This paper then summarizes the UDTIRI competition, organized in conjunction with IEEE Bigdata 2022. More details on our competition are available at ***/view/udtiri-workshop/bigdata-2022.

关键词： Roads Data acquisition Inspection Big Data Rough surfaces Digital twins

来源：评论

学校读者我要写书评

暂无评论

Sparse Kernel Regression with Coefficient-based `q−regularization

引用

Journal of Machine Learning Research 2019年 20卷

作者： Shi, Lei Huang, Xiaolin Feng, Yunlong Suykens, Johan A.K. Shanghai Key Laboratory for Contemporary Applied Mathematics School of Mathematical Sciences Fudan University Shanghai China Institute of Image Processing and Pattern Recognition Institute of Medical Robotics Shanghai Jiao Tong University MOE Key Laboratory of System Control and Information Processing Shanghai China Department of Mathematics and Statistics State University of New York at Albany New York United States Department of Electrical Engineering ESAT-STADIUS KU Leuven Kasteelpark Arenberg 10 LeuvenB-3001 Belgium

In this paper, we consider the `q−regularized kernel regression with 0 q−penalty term over a linear span of features generated by a kernel function. We study the asymptotic behavior of the algorithm under the framework of learning theory. The contribution of this paper is two-fold. First, we derive a tight bound on the `2−empirical covering numbers of the related function space involved in the error analysis. Based on this result, we obtain the convergence rates for the `1−regularized kernel regression which is the best so far. Second, for the case 0 ©c 2019 Lei Shi, Xiaolin Huang, Yunlong Feng, and Johan A.K. Suykens.

关键词： Regression analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：