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A feature selection method combined with ridge regression and recursive feature elimination in quantitative analysis of laser induced breakdown spectroscopy

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Plasma Science and Technology 2020年第7期22卷 11-20页

作者： Guodong WANG Lanxiang SUN Wei WANG Tong CHEN Meiting GUO Peng ZHANG State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016People’s Republic of China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016People’s Republic of China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169People’s Republic of China University of Chinese Academy of Sciences Beijing 100049People's Republic of China

In the spectral analysis of laser-induced breakdown spectroscopy,abundant characteristic spectral lines and severe interference information exist simultaneously in the original spectral ***,a feature selection method called recursive feature elimination based on ridge regression(Ridge-RFE)for the original spectral data is recommended to make full use of the valid information of *** the Ridge-RFE method,the absolute value of the ridge regression coefficient was used as a criterion to screen spectral characteristic,the feature with the absolute value of minimum weight in the input subset features was removed by recursive feature elimination(RFE),and the selected features were used as inputs of the partial least squares regression(PLS)*** Ridge-RFE method based PLS model was used to measure the Fe,Si,Mg,Cu,Zn and Mn for 51 aluminum alloy samples,and the results showed that the root mean square error of prediction decreased greatly compared to the PLS model with full spectrum as *** overall results demonstrate that the Ridge-RFE method is more efficient to extract the redundant features,make PLS model for better quantitative analysis results and improve model generalization ability.

关键词： laser-induced breakdown spectroscopy feature selection ridge regression recursive feature elimination quantitative analysis

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Pseudo-LiDAR for Visual Odometry

arXiv

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arXiv 2022年

作者： Deng, Huiying Wang, Guangming Feng, Zhiheng Jiang, Chaokang Wu, Xinrui Miao, Yanzi Wang, Hesheng Advanced Robotics Research Center AI Research Institute School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Department of Automation 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 Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

As one of the important tasks in the field of robotics and machine vision, LiDAR/visual odometry provides tremendous help for various applications such as navigation, location, etc. In the existing methods, LiDAR odometry shows superior performance, but visual odometry is still widely used for its price advantage. Conventionally, the task of visual odometry mainly rely on the input of continuous images. However, it is very complicated for the odometry network to learn the epipolar geometry information provided by the images. In this paper, the concept of pseudo-LiDAR is introduced into the odometry to solve this problem. The pseudo-LiDAR point cloud back-projects the depth map generated by the image into the 3D point cloud, which changes the way of image representation. Compared with the stereo images, the pseudo-LiDAR point cloud generated by the stereo matching network can get the explicit 3D coordinates. Since the 6 Degrees of Freedom (DoF) pose transformation occurs in 3D space, the 3D structure information provided by the pseudo-LiDAR point cloud is more direct than the image. Compared with sparse LiDAR, the pseudo-LiDAR has a denser point cloud. In order to make full use of the rich point cloud information provided by the pseudo-LiDAR, a projection-aware dense odometry pipeline is adopted. Most previous LiDAR-based algorithms sampled 8192 points from the point cloud as input to the odometry network. The projection-aware dense odometry pipeline takes all the pseudo-LiDAR point clouds generated from the images except for the error points as the input to the network. While making full use of the 3D geometric information in the images, the semantic information in the images is also used in the odometry task. The fusion of 2D-3D is achieved in an image-only based odometry. Experiments on the KITTI dataset prove the effectiveness of our method. To the best of our knowledge, this is the first visual odometry method using pseudo-LiDAR. Copyright © 2022, The Authors. A

关键词： Pipelines

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A 5G-Based Switching Method Between a Local controller and an Edge controller

A 5G-Based Switching Method Between a Local Controller and a...

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IEEE International Conference of intelligent Robotic and control Engineering (IRCE)

作者： Xiulian Wang Jinggao Lin Xi Jin Changqing Xia Chi Xu College of Automation and Electrical Engineering Shenyang Ligong University China 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

With the rapid development of edge computing, industrial automation has evolved a two-layer distributed computing architecture, including local controllers communicating through wired networks and edge controllers communicating wirelessly. The edge controllers in existing studies use WIFI, which has a limited working distance and requires independent network deployment, so they are unsuitable for future large-scale complex industrial production. At present, 5G technology is undergoing rapid development in the field of industrial automation, with wide coverage and excellent mobility, gradually becoming suitable for future large-scale and complex industrial production scenarios. Therefore, this paper proposed an SW5G method based on 5G, which combined the local controller with the edge controller. The controllers were switched according to the constantly changing 5G network transmission delay, thereby optimizing the overall system control performance. Finally, simulation experiments demonstrated good control performance of SW5G in various network scenarios.

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A Fast Conversion Method of Tube Coordinates

A Fast Conversion Method of Tube Coordinates

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作者： Hao Zhao Renbo Xia Yueling Chen Liming Tao Daixian Zhao Tianyu Zhang Key Laboratory of Networked Control System Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institute of Robotics and Intelligent Manufacturing Innovation Chinese Academy of Sciences University of Chinese Academy of Sciences

Inspired by the idea of the coordinate transformation of the robot arm, the tube structure is analogized to the robot arm structure, and the conversion method of the tube bend processing parameters LRA to the three-dimensional coordinate points is obtained. The method first regards the tube as a "mechanical arm";then, using the similarity of the LRA processing parameters and DH parameters, all the LRA parameters are converted into D-H parameters;finally, the D-H parameter method is applied to calculate the distance between each axis of the " mechanical arm ". If the first space coordinate point is defined as the origin of the base coordinate system (0, 0, 0), then the position of the origin of other coordinate systems in the base coordinate system can be obtained;It has been proved by experiments that this method fast and feasible.

关键词： Tube Coordinates Fast Conversion Method Mechanical Arm D-H Parameter Method

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Design and Implementation of OpenWSN Hardware Platform

Design and Implementation of OpenWSN Hardware Platform

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Algorithms, High Performance Computing and Artificial Intelligence (AHPCAI), International Conference on

作者： Shusheng Zhang Chuang Xie Jun Liu Chun Zhao Zhijia Yang Jizhi Mao College of Automation and Electrical Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

This paper proposes a new wireless sensor network hardware platform based on OpenWSN project launched by the University of California, Berkeley. The hardware platform's processor uses a 32-bit microcontroller (STM32F103RCT6) produced by STMicroelectronics (ST), and the wireless module uses the WISA470 chip. The final experimental results show that this platform can support the Open WSN project very well.

关键词： Wireless communication Radio frequency Wireless sensor networks Protocols Power supplies Microcontrollers Hardware

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TransVOS: Video object segmentation with transformers

arXiv

引用

arXiv 2021年

作者： Mei, Jianbiao Wang, Mengmeng Lin, Yeneng Yuan, Yi Liu, Yong Laboratory of Advanced Perception on Robotics and Intelligent Learning College of Control Science and Engineering Zhejiang University NetEase Fuxi AI Lab

Recently, Space-Time Memory Network (STM) based methods have achieved state-of-the-art performance in semi-supervised video object segmentation (VOS). A crucial problem in this task is how to model the dependency both among different frames and inside every frame. However, most of these methods neglect the spatial relationships (inside each frame) and do not make full use of the temporal relationships (among different frames). In this paper, we propose a new transformer-based framework, termed TransVOS, introducing a vision transformer to fully exploit and model both the temporal and spatial relationships. Moreover, most STM-based approaches employ two separate encoders to extract features of two significant inputs, i.e., reference sets (history frames with predicted masks) and query frame (current frame), respectively, increasing the models' parameters and complexity. To slim the popular two-encoder pipeline while keeping the effectiveness, we design a single two-path feature extractor to encode the above two inputs in a unified way. Extensive experiments demonstrate the superiority of our TransVOS over state-of-the-art methods on both DAVIS and YouTube-VOS datasets. Codes are available at https://***/sallymmx/***. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal encoding

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Vision based collision detection for a safe collaborative industrial manipulator

Vision based collision detection for a safe collaborative in...

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IEEE International Conference on Intelligence and Safety for robotics (ISR)

作者： Bruno Maric Fran Jurican Matko Orsag Zdenko Kovacic LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb Croatia

ISBN: (纸本)9781665438629;9781665411486

In this work we present an improved method for collision detection that extends the ability of collaborative systems to share the workspace between the operator and the robot. Our work is based on the state-of-the-art GPU-Voxels algorithm, with a dynamic swept volume method for collision detection that minimizes intervention in robot trajectories. We propose a sensor calibration method that allows multiple cameras to be placed around the robot to ensure coverage without shadows. In addition, we show how our previous work on advanced force control algorithms, which in combination with the collision detection algorithm presented, meets all safety requirements of the technical specification ISO/TS 15066. Our ultimate goal is to derive a framework for collaborative industrial manipulators, which are able to work side by side with people.

关键词： Heuristic algorithms Dynamics Collaboration Robot sensing systems Safety Trajectory Calibration

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Pedestrian Target Detection Model Based on Improved Yolov8

Pedestrian Target Detection Model Based on Improved Yolov8

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Artificial Intelligence and Electromechanical Automation (AIEA), International Conference on

作者： Jinglun Huang Jianan Liang Yongjun Cao School of Electronics and Information Engineering Wuyi University Jiangmen Guangdong China Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent Manufacturing GDAS Guangzhou Guangdong China South China Robotics innovation Research Institute Foshan Guangdong China School of Mechanical & Automotive Engineering South China University of Technology Guangzhou Guangdong China

ISBN: (数字)9798350366174

ISBN: (纸本)9798350366181

Dense pedestrian detection is a key technology in public intelligent surveillance. It identifies the location and number of pedestrians in videos through object detection methods, thereby achieving intelligent surveillance of crowds. However, in crowded scenes, due to occlusion and small pedestrian targets, it is easy to miss pedestrians. To solve this problem, this paper proposes an improved YOLOv8 detection algorithm, YOLOv-8FastTCD. Firstly, the FasterNet module is used to replace the backbone network. Secondly, a task collaborative dynamic detection head (TCDDH) is introduced after the neck network. The performance of this model on the CrowdHuman dense pedestrian detection dataset has been improved, with mAP 50 and $\mathrm{mAP}_{50-95}$ reaching $\mathbf{7 8. 4 \%}$ and 51.5% respectively, which are 2.1% and 2.0% higher than the original YOLOv8n model.

关键词： Performance evaluation Pedestrians Shape Computational modeling Surveillance Object detection Real-time systems Neck Computational efficiency Videos

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A Novel Dynamically Differentiated Access Scheme for Massive Grant-Free NOMA

A Novel Dynamically Differentiated Access Scheme for Massive...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Yitian Wang Meng Zheng Haibin Yu Wei Liang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665454698

Facing the dual challenges of massive access and time-sensitive traffics, grant-free non-orthogonal multiple access (GF-NOMA) emerges as a promising technology for implementing massive ultra-reliable and low-latency communications (mURLLC). In this paper, we propose a differentiated power level access (DPLA) policy that exploits the correlations among power levels of GF-NOMA, and implement DPLA by a dynamically distributed GF-NOMA framework. Further, a closed-form expression to the reliability of DPLA is analytically derived and the optimal framework parameters to maximize reliability are obtained. Finally, considering the traffic variation over time, we propose a dynamically-distributed differentiated-layered transmission $(\mathrm{D}^{3}$ LT) algorithm to improve the reliability online. Simulation results show that the proposed scheme in this work outweighs existing schemes in transmission reliability.

关键词： NOMA Vehicular and wireless technologies Correlation Closed-form solutions Simulation Heuristic algorithms Reliability

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Robotic Electrospinning Actuated by Non-Circular Joint Continuum Manipulator for Endoluminal Therapy

Robotic Electrospinning Actuated by Non-Circular Joint Conti...

引用

2021 IEEE International Conference on robotics and Automation, ICRA 2021

作者： Wu, Zicong Lou, Chuqian Jin, Zhu Huang, Shaoping Liu, Ning Zou, Yun Kovac, Mirko Gao, Anzhu Yang, Guang-Zhong The Institute of Medical Robotics Department of Bioengineering Shanghai Jiao Tong University Shanghai200240 China Imperial College London Empa-Swiss Federal Laboratories for Materials Science and Technology United Kingdom Limited 999077 Hong Kong Aerial Robotics Laboratory Imperial College London LondonSW7 2AZ United Kingdom The Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China The Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781728190778

Electrospinning has exhibited excellent benefits to treat the trauma for tissue engineering due to its produced micro/nano fibrous structure. It can effectively adhere to the tissue surface for long-term continuous therapy. This paper develops a robotic electrospinning platform for endoluminal therapy. The platform consists of a continuum manipulator, the electrospinning device, and the actuation unit. The continuum manipulator has two bending sections to facilitate the steering of the tip needle for a controllable spinning direction. Non-circular joint profile is carefully designed to enable a constant length of the centreline of a continuum manipulator for stable fluid transmission inside it. Experiments are performed on a bronchus phantom, and the steering ability and bending limitation in each direction are also investigated. The endoluminal electrospinning is also fulfilled by a trajectory following and points targeting experiments. The effective adhesive area of the produced fibre is also illustrated. The proposed robotic electrospinning shows its feasibility to precisely spread more therapeutic drug to construct fibrous structure for potential endoluminal treatments. © 2021 IEEE

关键词： Electrospinning

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