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第三十八届中国控制会议

作者： Wang Pu Zeng Wenhao Gao Xuejin Faculty of Information Technology Beijing University of Technology Engineering Research Center of Digital Community Beijing Laboratory For Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

The common energy efficiency model of chiller in subway station has nonlinear interference, which leads to low prediction accuracy and reliability. To solve the above problems, this paper proposes a model of chiller efficiency prediction based on error correction. This model focuses on the error, trains the historical data of prediction error by SVR, and then corrects the prediction result of traditional model to get the final prediction value of energy efficiency. Through the verification of operation data from air conditioning units on a beijing subway platform, the results show that this model is superior to the traditional model, the average relative error of predictive value decreased from 4.04*10 to 6.69*10.

关键词： chiller support vector machine error correction thermodynamics

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Review of machine-vision-based plant detection technologies for robotic weeding

Review of machine-vision-based plant detection technologies ...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Li, Nan Zhang, Xiaoguang Zhang, Chunlong Ge, Luzhen He, Yong Wu, Xinyu Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen518055 China Shenzhen University Shenzhen518060 China China Agricultural University College of Engineering Beijing100083 China

ISBN: (纸本)9781728163215

Controlling weeds with reduced reliance on herbicides is one of the main challenges to move toward a more sustainable agriculture. Robotic weeding is a thought to be a viable way to reduce the environmental loading of agrochemicals while keeping the operation efficiency high. One of the key technologies for performing robotic weeding is automatic detection of crops and weeds in fields. This paper presents an overview on various methods for detecting plants based on machine vision, mainly concentrating on two main challenges: dealing with changing light and crop/weed discrimination. To overcome the first challenge, both physical and algorithmic methods have been proposed. Physical methods can result in a more cumbersome machine while algorithmic methods are less robust. For crop/weed discrimination, deep-learning-based methods have shown obvious advantages over traditional methods based on hand-crafted features. However, traditional methods still hold some merits that can be leveraged to deep-learning-based methods. With the fast development of hardware technologies, researchers should take full advantage of advanced hardware to ease the algorithm design. In the future, the identification of crops and weeds can be more accurate and fine-grained with the support of online databases and computing resources based on the advances in artificial intelligence and communication technologies. © 2019 IEEE.

关键词： Crops

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Obstacle avoidance of manipulators based on improved artificial potential field method

Obstacle avoidance of manipulators based on improved artific...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Li, Hao Wang, Zhiyang Ou, Yongsheng Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergic Systems Shenzhen Institutes of Advanced Technology China

ISBN: (纸本)9781728163215

Obstacle avoidance is a key problem of robot motion planning. This paper introduces an improved method to realize obstacle avoidance of manipulators based on artificial potential field method which offers a relatively fast and effective way to solve the problem. We establish the attractive potential field function of the goal and the repulsive potential filed functions of obstacles in the workspace instead of the configuration space. Then a series of control points on the manipulator are chosen to be influenced by the total potential. A policy is proposed that only the end point is attracted to the goal while all selected points are repulsed by obstacles. Afterwards, we transfer the potential force of each point in workspace into the moment in configuration space to make the manipulator move by iteration of joint angles. The effectiveness of the method is confirmed by simulation experiments. © 2019 IEEE.

关键词： Motion planning

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Comparative Study of Four Speed Controllers of Brushless DC Motors for Industrial Applications

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IFAC-PapersOnLine 2020年第5期53卷 59-64页

作者： Tariku Sinshaw Tamir Gang Xiong Zhen Shen Xiaoyan Gong Sheng Liu Ehtisham Lodhi Li Wan Xisong Dong State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing 100049 China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Donggguan 523808 China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China Ten Dimensions (Guangdong) Technology Co. Ltd. Foshan 528225 China

Direct current (DC) motors are one of the most important kind of motors and are widely used in robotic and industrial applications. Recently, there have been significant efforts to develop direct current (DC) motors in an attempt to control speed of motors. However, conventional controlling approaches perform undesirably in terms of stability and quick response. Therefore, this paper presents a hybrid intelligent controller configuration for optimized speed control of brushless direct current (BLDC) motors in a factory supervisory control data acquisition (SCADA) system. We compare this hybrid intelligent controller with a conventional PID controller, fuzzy logic controller (FLC), and artificial neural network model reference controller (ANNMRC) in MATLAB , and the results show that the hybrid (neuro-fuzzy) controller performs superior in terms of stability, speed trajectory tracking capability, fast response, and simplicity for implementation.

关键词： BLDC motor fuzzy logic controller (FLC) artificial neural network model reference controller (ANNMRC) hybrid (neuro-fuzzy) control

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Random Occlusion Recovery with Noise Channel for Person Re-identification 16th

Random Occlusion Recovery with Noise Channel for Person Re-i...

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16th International Conference on intelligent computing, ICIC 2020

作者： Zhang, Kun Wu, Di Yuan, Changan Qin, Xiao Wu, Hongjie Zhao, Xingming Zhang, Lijun Du, Yuchuan Wang, Hanli Institute of Machine Learning and Systems Biology School of Electronics and Information Engineering Tongji University Shanghai China Guangxi Academy of Science Nanning530025 China School of Computer and Information Engineering Nanning Normal University Nanning530299 China School of Computer Science and Technology Soochow University Suzhou215006 China School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou215009 China Fudan University Shanghai200433 China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Ministry of Education Shanghai China Collaborative Innovation Center of Intelligent New Energy Vehicle and School of Automotive Studies Tongji University Shanghai201804 China The Key Laboratory of Road and Traffic Engineering of the Ministry of Education Department of Transportation Engineering Tongji University Shanghai201804 China Department of Computer Science and Technology the Key Laboratory of Embedded System and Service Computing and Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China

ISBN: (纸本)9783030607982

Person re-identification, as the basic task of a multi-camera surveillance system, plays an important role in a variety of surveillance applications. However, the current mainstream person re-identification model based on deep learning requires a lot of labeled data, which takes a lot of time and manpower. In this study, we proposed a person re-identification method based on random occlusion recovery with noise channel. We add random occlusion blocks to the original image, use the GAN model for repair, and use the repaired image to expand the original training set. After that, the generated image is adjusted through the noise channel. Finally, we use the enhanced data set to train the baseline model. Our model achieves the state-of-the-art on Market-1501 dataset, proving that the method is effective. © 2020, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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Feature subset discernibility evaluation method for upper limb rehabilitation training based on the discernibility of relative distance 15

Feature subset discernibility evaluation method for upper li...

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15th IEEE International Conference on Mechatronics and Automation, ICMA 2018

作者： Zuo, Guoyu Xu, Zhaokun Lu, Jiahao Faculty of Information Technology Beijing University of Technology Beijing1000124 China Beijing Key Laboratory of Computing Intelligence and Intelligent Systems Beijing1000124 China

ISBN: (纸本)9781538660720

In this paper, a feature subset discernibility hybrid evaluation method based on the discernibility of relative distance and support vector machine (DRD-SVM) is proposed for the feature selection problem of the upper limb rehabilitation training motion of Brunnstrom 4-5 stage patients, in which a relative distance is introduced into evaluating the discernibility between classes considering the joint effect of both candidate and selected features. First, a feature subset search strategy is used to search a set of candidate feature subsets. Then the DRD is used to evaluate the candidate feature subsets, the best subset is selected as a new selected feature subset, and the feature subset with the best performance of SVM classification is selected as the optimal feature subset. Finally, feature selection experiment was carried out on upper limb routine rehabilitation training samples of the Brunnstrom 4-5 stage. The experimental results shows that, compared with the F-score method and the DFS one, the proposed method can obtain the feature subsets with higher accuracy and smaller feature dimension, which improves its effectiveness and feasibility. © 2018 IEEE.

关键词： Support vector machines

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Variational optical flow based velocity estimation for omni-directional intelligent wheelchair

Variational optical flow based velocity estimation for omni-...

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作者： Shan, Jichao Li, Xiuzhi Jia, Songmin Lu, Xingyang Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9781538636749

To measure the velocity for the omni-directional intelligent wheelchair for the depth research on control and improve the measured accuracy and computational efficiency, the variational optical flow based velocity estimation method is used in this paper. Firstly, an improved energy functional model which combines a brightness constancy assumption, a gradient constancy assumption, a Laplacian constancy assumption and a discontinuity-preserving spatio-temporal smoothness constraint is employed to improve the accuracy of optical flow estimation;Then, a planar optical flow model based improved voting Random Sample Consensus(RANSAC) method is presented to remove heterogeneous optical flow vectors produced by non-uniform ambient illumination, local motion blur and chaotic surrounding environment. Finally, aiming at the installation attitude of the camera, an effective method of camera attitude adjustment is introduced to simplify the spatial coordinate system transformation and solve the model. This paper has realized the velocity estimation of the wheelchair by real-time acquisition of images in the framework of the Robot Operating system(ROS). Experimental results showed that the wheelchair velocity estimation method performed robustly in the presence of chaotic surrounding environment through the above improvements. © 2017 IEEE.

关键词： Machine vision Motion estimation Optical flow ROS Voting RANSAC

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A method of cliff detection in robot navigation based on multi-sensor

A method of cliff detection in robot navigation based on mul...

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IEEE International Conference on Real-time computing and Robotics (RCAR)

作者： Zhilong Su Can Wang Yuxiao Li Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence Synergic Systems Shenzhen Institutes of Advanced Technolog Shenzhen China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

This paper proposed a method to detect cliff edge by using an RGB-D camera, and then to fuse the cliff information with LiDAR, finally to provide navigation information for robot autonomous exploration and autonomous movement. Compared with the prior methods which set sonar or infra-red sensor in the bottom of the robot, our method could detect cliff earlier by set the RGB-D camera forward. In cliff detection, we use region growing algorithm and the normal vector of plane to segment out ground plane in point cloud, then extract the boundary points of ground, and we proposed an Edge Point Filter (EPF) to get the edge points of cliff, then use the edge points to simulate LiDAR data and combine with real LiDAR data to mark the untraversable area. We verified the practicability of this method in simulation, and verified the accuracy with real sensors.

关键词： Laser radar Robots Three-dimensional displays Robot sensing systems Indexes Cameras Image edge detection

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Adaptive GridMap Building Algorithm for Mobile Robot Based on Multiway Tree

Adaptive GridMap Building Algorithm for Mobile Robot Based o...

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2018 International Conference on Electrical Engineering, Control and Robotics, EECR 2018

作者： Zhou, Jing Ruan, Xiaogang Dong, Pengfei Zhang, Jingjing Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

In order to solve the problem that uniform grid map occupies large storage space in the process of large-scale map creation, a new adaptive grid map building algorithm based on multiway tree is proposed. The environment map is divided into nine grids. The algorithm determines whether the grid is completely occupied, partially occupied or vacant. Then the part occupied gridsare further subdivided into smaller grids. The algorithm continues to determine whether the smaller grid is completely occupied, partially occupied or *** the above segmentation process until the entire map search is completed and the accuracy requirements are met. Finally, the scale of grid map does not depend on human experience but presenting adaptive characteristics. The algorithm is compared with the uniform grid *** simulation results show that the algorithm has *** with the uniform scale raster map, itgreatly saves the storage space. © The Authors, published by EDP Sciences, 2018.

关键词： Forestry

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Position-based visual servo control of intelligent wheelchair/bed docking

Position-based visual servo control of intelligent wheelchai...

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2018 IEEE International Conference on Information and Automation, ICIA 2018

作者： Li, Xiuzhi Liang, Xingnan Fan, Jinhui Jia, Songmin Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9781538680698

For the automatic docking problem of a Mecanum-wheeled omnidirectional intelligent wheelchair/bed system, a visual servo control method which is based on position feedback is proposed in this paper. When it is docked with the auxiliary bed, the intelligent wheelchair firstly collects and identifies special landmark on the auxiliary bed through the vehicle vision system;Then the relative pose between the wheelchair and the auxiliary bed is determined according to the transformation between the camera coordinate system and the bed coordinate system based on an artificial landmark;Finally, the intelligent wheelchair is controlled to travel from the initial position to the desired position by position-based visual servo (PBVS) control method and completes docking task between the intelligent wheelchair and the auxiliary bed. The implementation of visual docking control for the intelligent wheelchair is based on the Robotic Operating system (ROS) platform. Experimental results are presented to validate the practicality and effectiveness of the proposed method in this paper. © 2018 IEEE.

关键词： Visual servoing

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