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arXiv 2020年

作者： Jiang, Jun Li, Zhengguo Xie, Shoulie Wu, Shiqian Zeng, Liangcai Key Laboratory of Metallurgical Equipment and Control Technology Wuhan University of Science and Technology Wuhan China Institute for Infocomm Research Singapore Institute of Robotics and Intelligent Systems School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

It is challenging to align multi-exposed images due to large illumination variations, especially in presence of saturated regions. In this paper, a novel image alignment algorithm is proposed to cope with the multi-exposed images with saturated regions. Specifically, the multi-exposed images are first normalized by using intensity mapping functions (IMFs) in consideration of saturated pixels. Then, the normalized images are coded by using the local binary pattern (LBP). Finally, the coded images are aligned by formulating an optimization problem by using a differentiable Hamming distance. Experimental results show that the proposed algorithm outperforms state-of-the-art alignment methods for multi-exposed images in terms of alignment accuracy and robustness to exposure *** Codes CS © 2020, CC0.

关键词： Hamming distance

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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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A Guide for Human Walking Model and control——Insights from Mechanical Property Analysis of Human Walking

A Guide for Human Walking Model and Control——Insights from...

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第32届中国控制与决策会议

This paper aims to establish the simplest human walking model and provide a guide for controlling biped ***,a human motion capture system was utilized to sample the motion data of human walking and a representative subject was ***,one of the simplest human walking model was set *** mechanical property analysis of human walking was done based on the established walking model via ***,the feasibility and effectiveness of proposed walking model were validated by numerical ***,the intrinsical relationships among human walking,biped walking model and control were discussed to provide a guide and insight for controlling biped robots.

关键词： Human Walking Model Biped Robots Leg Stiffness Legged Locomotion Model and control

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End-to-End 3D Point Cloud Learning for Registration Task Using Virtual Correspondences

End-to-End 3D Point Cloud Learning for Registration Task Usi...

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2020 IEEE/RSJ International Conference on intelligent Robots and Systems (IROS)

作者： Huanshu Wei Zhijian Qiao Zhe Liu Chuanzhe Suo Peng Yin Yueling Shen Haoang Li Hesheng Wang The Chinese University of Hong Kong T Stone Robotics Institute Hong Kong Shanghai Jiao Tong University China University of Cambridge United Kingdom Carnegie Mellon University 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 Shanghai China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

3D Point cloud registration is still a very challenging topic due to the difficulty in finding the rigid transformation between two point clouds with partial correspondences, and it's even harder in the absence of any initial estimation information. In this paper, we present an end-to-end deep-learning based approach to resolve the point cloud registration problem. Firstly, the revised LPD-Net is introduced to extract features and aggregate them with the graph network. Secondly, the self-attention mechanism is utilized to enhance the structure information in the point cloud and the cross-attention mechanism is designed to enhance the corresponding information between the two input point clouds. Based on which, the virtual corresponding points can be generated by a soft pointer based method, and finally, the point cloud registration problem can be solved by implementing the SVD method. Comparison results in ModelNet40 dataset validate that the proposed approach reaches the state-of-the-art in point cloud registration tasks and experiment resutls in KITTI dataset validate the effectiveness of the proposed approach in real applications.

关键词： Three-dimensional displays Aggregates Pose estimation Feature extraction Task analysis intelligent robots

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Position Sensorless control of Permanent Magnet Synchronous Motor Based on Adaptive Sliding Mode Observer

Position Sensorless Control of Permanent Magnet Synchronous ...

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Chinese Automation Congress (CAC)

作者： Tao Zhang Yingjie Xiong Bolun Wang Hongyu Yan Xiyou Chen School of Electrical Engineering Dalian University of Technology Dalian China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China College Of Information Science and Engineering Northeastern University Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (纸本)9781665426480

Permanent magnet synchronous motors(PMSM) are popular in AC motor applications due to their small size, high efficiency. They have appeared widely in various areas of life. Due to the high-frequency chattering problem caused by sliding mode observer sensorless control of PMSM, an SMO with piecewise control function is designed in this paper. At the same time, based on the back EMF output of the SMO, the gain of the SMO is adapted to reduce the system bucket vibration problem caused by the conventional SMO. Finally, a simulation experiment was carried out in MATLAB/SIMULINK and compared with the conventional SMO. The results show that the improved SMO has achieved a better control effect.

关键词： Vibrations Adaptation models AC motors Force Sensorless control Observers Permanent magnet motors

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Spherical interpolated convolutional network with distance-feature density for 3D semantic segmentation of point clouds

arXiv

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arXiv 2020年

作者： Wang, Guangming Yang, Yehui Zhang, Huixin 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 Computer Science and Technology University of Cambridge United Kingdom

The semantic segmentation of point clouds is an important part of the environment perception for robots. However, it is difficult to directly adopt the traditional 3D convolution kernel to extract features from raw 3D point clouds because of the unstructured property of point clouds. In this paper, a spherical interpolated convolution operator is proposed to replace the traditional grid-shaped 3D convolution operator. This newly proposed feature extraction operator improves the accuracy of the network and reduces the parameters of the network. In addition, this paper analyzes the defect of point cloud interpolation methods based on the distance as the interpolation weight and proposes the self-learned distance-feature density by combining the distance and the feature correlation. The proposed method makes the feature extraction of spherical interpolated convolution network more rational and effective. The effectiveness of the proposed network is demonstrated on the 3D semantic segmentation task of point clouds. Experiments show that the proposed method achieves good performance on the ScanNet dataset and Paris-Lille-3D dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Research on Collaboration Method of Edge IoT Agent Based on Actor Model

Research on Collaboration Method of Edge IoT Agent Based on ...

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Power and Energy Engineering (ICPEE), International Conference on

作者： Bowen Zhang Weiwei Miao Lei Wei Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Information & Telecommunication Branch State Grid Jiangsu Electric Power Co. Ltd. Nanjing China State Grid Jiangsu Electric Power Co. Ltd. Nanjing China

ISBN: (纸本)9781665420471

Focusing on the resource constrained IoT agent collaboration requirements at the edge of the power Internet of things, this paper proposes an edge agent collaborative computation method based on Actor model to satisfy the rapid processing and response requirements of large-scale data in the perception layer of the power Internet of things. Through a unified programming model, this paper can divide the collection and analysis of sensing data in the sensing layer of the power Internet of things into functional components, which can be deployed in different edge IoT agents, to improve the rapid processing ability of edge-side data. At the same time, the components achieve the function cooperation through the message passing mechanism. Finally, this paper implements the proposed scheme based on Akka framework, and designs the edge IoT agent collaborative computing prototype. The prototype system experiments show that the proposed scheme can split the complex services with high resource requirements into different components and deploy them in different edge IoT agents. The proposed method can improve the resource utilization and data processing capacity of the edge IoT agent of the power Internet of things, while ensuring the real-time requirements of edge service analysis.

关键词： Computational modeling Message passing Collaboration Prototypes Programming Data models Real-time systems

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Design and Analysis of A Novel AFPM with Opposite-Rotation Dual Rotors 4

Design and Analysis of A Novel AFPM with Opposite-Rotation D...

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4th IEEE International Future Energy Electronics Conference, IFEEC 2019

作者： Wei, Mengfei Zhang, Chi Chen, Jinhua Xu, Chenxia Chinese Academy of Sciences Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology of Zhejiang Province Ningbo Institute of Materials Technology and Engineering Ningbo China University of Chinese Academy of Sciences Beijing China Phase Motion Control Ningbo Ltd. China

ISBN: (纸本)9781728131535

This paper proposes a novel opposite-rotation dual-rotor axial flux permanent-magnet machine (ORDR-AFPM) for underwater vehicle counter-rotation propeller propulsion system. The structure of the machine mainly consists of dual identical surface-mounted PM rotors, dual sets of concentrated windings and single stator sandwiched in between the dual rotors. The dual rotors operate independently like dual conventional machines but toward opposite directions. For the purpose of exploring the interaction between the dual rotors and verify the feasibility of the machine, the flux distribution in the dual air gaps is analyzed by magnetic equivalent circuit (MEC). Meanwhile, finite-element method (FEM) is also used to confirm the validity of the theoretical analysis. During the process of machine design, the axial magnetic force is analyzed by using Maxwell stress tensor and the main design parameters of the machine get optimized. © 2019 IEEE.

关键词： Finite element method

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Multi-Person Pose Estimation via Learning Feature Integration 4

Multi-Person Pose Estimation via Learning Feature Integratio...

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2019 4th Annual International Conference on Information System and Artificial Intelligence, ISAI 2019

作者： Hu, Xiaomei Tian, Jiahao Qiao, Huixiang Wang, Minjie Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai China Institute of Materials Technology and Engineering CAS Ningbo315201 China School of Electronic Information and Control Engineering Chang'An University Xi'an Shaanxi713100 China

Human pose estimation is a fundamental but challenging task in computer vision. Although batch normalization is widely used for deep learning, feature extraction in deep convolutional neural networks (DCNN) is still not well explored. In this work, we propose a pose encoding module (PEM) to enhance the learning ability and generalization ability of feature extraction. Given input images, PEM integration instance normalization and batch normalization, combining them in an appropriate way to learn to capture and eliminate appearance changes while maintaining the distinction between learning features can be seen as an integration and adjustment of global information. In addition, we use a simple and efficient up-sampling strategy to recover high-resolution representations for predicting more accurate human keypoint heatmaps, which has achieved better performance than the average network in recent missions. We studied our approach on a standard benchmark for human pose estimation. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Feature extraction

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Adaptive tracking control of flapping wing micro-air vehicles with averaging theory

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CAAI Transactions on Intelligence Technology 2018年第1期3卷 18-27页

作者： Chen Qian Yongchun Fang Institute of Robotics and Automatic Information Systems College of Computer and Control Engineering Tianjin 300353People's Republic of China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin 300353 People's Republic of China

An input constrained adaptive tracking controller is designed for flapping micro aerial vehicles, wherein the moving averaging filter is adopted to estimate the averaged states of the system. Specifically, in the outer loop controller, an observer is constructed to estimate the disturbances within the system. Moreover, the constrained thrust is designed to keep the frequency in a proper region so as to meet the requirement of average estimation. Then, a tracking differentiator is used to provide trackable trajectories for the inner loop. Subsequently, a new quaternion- based hybrid attitude tracking controller is designed which successfully deals with high-frequency noises and avoids possible chattering. As supported by mathematical analysis, the proposed control strategy guarantees the uniform ultimate boundedness of the closed-loop system, and it keeps the control torques within the permitted range to meet the application requirement. At last, numerical simulations are carried out to support the validity of the proposed controller, whose results are satisfactory even when the thrust and torques are saturated.

关键词：飞行器跟踪器人工智能发展现状

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