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4th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Liang, Congyuan Liu, Chao Liu, Xiaofeng Cheng, Long Yang, Chenguang South China Univ Technol Sch Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Peoples R China Univ Montpellier CNRS Dept Robot LIRMMUMR5506 161 Rue Ada F-34095 Montpellier France Changzhou Key Lab Robot & Intelligent Technol Changzhou 213022 Peoples R China Hohai Univ Jiangsu Key Lab Special Robots Changzhou 213022 Peoples R China Hohai Univ Coll IoT Engn Changzhou 213022 Peoples R China Chinese Acad Sci Inst Automat Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Univ West England Bristol Robot Lab Bristol BS16 1QY Avon England

ISBN: (纸本)9781728100647

This work develops a novel robot teleoperation system based on mixed reality. Combined with Leap Motion and HoloLens, the system is able to offer a better operate experience by allowing the operator to teleoperate a robot within a mixed reality scene. Besides, we also design a simple writing task in this paper, which verifies the proposed system's validity.

关键词： Robot kinematics Virtual reality Manipulators Conferences Mechatronics Task analysis

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MPC Control and Path Planning of Omni-directional Mobile Robot with Potential Field Method

MPC Control and Path Planning of Omni-directional Mobile Rob...

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

作者： Liu, Xiaofeng Chen, Hailin Wang, Chengcheng Hu, Fang Yang, Xianqiang Hohai Univ Coll IoT Engn Changzhou 213022 Peoples R China Changzhou Key Lab Robot & Intelligent Technol Changzhou 213022 Peoples R China Jiangsu Key Lab Special Robots Changzhou 213022 Peoples R China Changzhou Vacat Inst Engn Sch Electromech & Automobile Engn Changzhou 213164 Peoples R China Harbin Inst Technol Res Inst Intelligent Control & Syst Harbin 150080 Heilongjiang Peoples R China

ISBN: (纸本)9781538668696

The navigation of a omnidirectional mobile robot (OMR) by using a model predictive control (MPC) strategy through the path which is obtained by the potential field method is presented. The OMR is controlled with the three independent stepper motors, which makes it possible to go forward in any expected direction with three Mecanum wheels. The main motivation to use MPC is that it has the an advantage in handling state variable constraints and control variable constraints in practical situations. The past and future control inputs combined with present responses are predicted through the kinematics model of OMR and are optimized at regular interval with respect to a performance index. Simulation results show that OMR moves along the desired and predefined trajectory accurately.

关键词： Mobile robots Mathematical model Wheels Robot kinematics Force Path planning

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A hybrid NSGA-II for matching biomedical ontology 14th

A hybrid NSGA-II for matching biomedical ontology

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14th International Conference on intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2018

作者： Xue, Xingsi Chen, Jie Chen, Junfeng Chen, Dongxu College of Information Science and Engineering Fujian University of Technology FuzhouFujian350118 China Intelligent Information Processing Research Center Fujian University of Technology FuzhouFujian350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology FuzhouFujian350118 China Fujian Key Lab for Automotive Electronics and Electric Drive Fujian University of Technology FuzhouFujian350118 China College of IOT Engineering Hohai University ChangzhouJiangsu China Fujian Medical University Union Hospital FuzhouFujian350001 China

ISBN: (纸本)9783030037444

Over the recent years, ontologies are widely used in the biomedical domains. However, biomedical ontology heterogeneity problem hamper the cooperation between intelligent applications based on biomedical ontologies. It is crucial to establish correspondences between the heterogeneous biomedical concepts in different ontologies, which is so-called biomedical ontology matching. Approaches based on Multi-Objective Evolutionary Algorithm (MOEA), such as NSGA-II, are emerging as a new methodology to solve the ontology matching problem. In this paper, to further improve the quality of biomedical ontology alignments, a hybrid NSGA-II is proposed, which modifies the knee solutions in the Pareto front by using a local search method. Experiment utilizes two biomedical ontology matching tracks provided by Ontology Alignment Evaluation Initiative (OAEI 2017). The experimental results show that our approach outperforms the participants of OAEI 2017 and NSGA-II based ontology matching technique. © Springer Nature Switzerland AG 2019.

关键词： Ontology

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A Novel Adaptive Sliding Mode Control for Manipulator with External Disturbance

A Novel Adaptive Sliding Mode Control for Manipulator with E...

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第37届中国控制会议

作者： Sen Jiang Jing Zhao Fei Xie Jian Fu Xian Wang Zeyun Li School of Automation Nanjing University of Posts and Telecommunications Jiangsu Engineering Lab for Intelligent IOT Robots Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing School of Electrical and Automation Engineering Nanjing Normal University College of Energy and Power Engineering Nanjing University of Science and Technology

In this paper, a sliding mode control method for manipulator in the presence of external disturbance is addressed. Firstly, the dynamic model of n-joint manipulator system is introduced. Secondly, aiming at a manipulator system with disturbance, a novel dynamic sliding mode controller based on adaptive technique is proposed, in which the parameter of external disturbance is estimated and updated by online adaptive method. Further, the stability of the overall system under this controller is verified based on Lyapunov theorem. Besides, through this method, there is no need to obtain the precise value of disturbance. Finally,experimental results demonstrate that the controller proposed in this work has strong robustness for disturbance, meanwhile can effectively reduce the chattering.

关键词： Dynamic Sliding Mode Control Adaptive Control Manipulator Disturbance

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Trajectory tracking of powered parafoil based on characteristic model based all-coefficient adaptive control

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Journal of Central South University 2017年第5期24卷 1073-1081页

作者： TAN Pan-long SUN Qing-lin JIANG Yu-xin ZHU Er-lin CHEN Zeng-qiang HE Ying-ping Intelligent Robots Key Lab of Tianjin College of Computer and Control EngineeringNankai UniversityTianjin 300071China School of Electricity&Information Engineering Jiangsu University of TechnologyChangzhou 213001China Hongwei Aircraft Limited Corp. Xiangyang 441022China

One of the primary difficulties in using powered parafoil(PPF) systems is the lack of effective trajectory tracking controllers since the trajectory tracking control is the essential operation for PPF to accomplish autonomous tasks. The characteristic model(CM) based all-coefficient adaptive control(ACAC) designed for PPF systems in horizontal and vertical trajectory control is proposed. The method is easy to use and convenient to adjust and test. Just a few parameters are adapted during the control process. In application, vertical and horizontal CMs are designed and ACAC controllers are constructed to control vertical altitude and horizontal trajectory of PPF based on the proposed CMs, respectively. Result analysis of different simulations shows that the applied ACAC control method is effective for trajectory tracking of the PPF systems and the approach guarantees the transient performance of the PPF systems with better disturbance rejection ability.

关键词： powered parafoil (PPF) characteristic model (CM) all-coefficient adaptive control (ACAC) trajectory tracking

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Multi-Channel Features Spatio-Temporal Context Learning for Visual Tracking

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IEEE ACCESS 2017年 5卷 12856-12864页

作者： Zhou, Xiaoqin Liu, Xiaofeng Yang, Chenguang Jiang, Aimin Yan, Bin Hohai Univ Coll IoT Engn Changzhou Key Lab Robot & Intelligent Technol Changzhou 213022 Peoples R China Hohai Univ Jiangsu Key Lab Special Robots Changzhou 213022 Peoples R China Swansea Univ Zienkiewicz Ctr Computat Engn Swansea SAL 8EN W Glam Wales Shandong Univ Sci & Technol Coll Elect Commun & Phys Qingdao 266590 Peoples R China

Visual tracking is a challenging issue in surveillance, human-computer Interaction, and intelligent robotics, among others. Managing appearance changes of the target object, illumination changes, rotations, non-rigid deformations, partial or full occlusions, background clutter, fast motion, and so forth is generally difficult. Among the numerous existing trackers, the correlation-filter-based tracker can achieve appealing performance with a fast speed for fast Fourier transform. Motivated by this property, the spatio-temporal context (STC) learning algorithm was proposed with the consideration of the information from the context around the target, and this algorithm achieved good results. However, STC only utilizes the overall intensity information. In this paper, we propose a multi-channel features STC learning algorithm with an improved scale-adaptive scheme. Our algorithm integrates powerful features, including Histogram of Oriented Gradients and color naming, using kernel methods on the basis of the STC algorithm to further enhance the overall tracking performance. Extensive experimental results obtained from various benchmark data sets demonstrate that the proposed tracker is promising for various challenging scenarios and maintains real-time performance at an average speed of 78 frames/s. According to the test results, our algorithm outperforms the STC algorithm and achieves performance that is competitive with the state-of-the-art algorithms.

关键词： Object tracking kernel methods correlation filters fast Fourier transform

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P-12.1: Lighting effects, light distribution matters

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SID Symposium Digest of Technical Papers 2019年第S1期50卷

作者： Ling Xia Tingting Zhang Xiaofeng Liu Sylvia C. Pont College of IoT Engineering Hohai University Changzhou Key Laboratory of Robotics and Intelligent Technology Jiangsu Key laboratory of Special Robot Technology Changzhou China Department of Industrial Design Perceptual Intelligence lab Delft University of Technology Delft The Netherlands

The interaction between light and its surroundings (i.e. the geometry and materials) shapes the lighting distribution and determines the appearance of scenes and its visual experiences. In this study, we introduced the concept of light distribution solids by distinguishing luminance distribution solids and illuminance distribution solids. It is helpful to understand the spatial and form-giving lighting effects on objects' appearance. Furthermore, this study together with our previous study (Xia, Pont et al. 2016, Xia, Pont et al. 2016) provide theoretical basis for the exploration of extracting photometry parameters out of HDR panoramic photographs of scenes.

关键词： Lighting effects lighting distribution luminance distribution solids illuminance distribution solids light density light diection light diffuseness HDR panoramic photogrphs

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Exploration of Muscle Fatigue Effects in Bioinspired Robot Learning from sEMG Signals

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COMPLEXITY 2018年第1期000卷

作者： Wang, Ning Xu, Yang Ma, Hongbin Liu, Xiaofeng Plymouth Univ Sch Comp Elect & Math Plymouth PL4 8AA Devon England Chinese Univ Hong Kong Shenzhen Res Inst Shatin Hong Kong Peoples R China South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China Beijing Inst Technol Sch Automat Zhong Guan Cun South St Beijing 100081 Peoples R China Changzhou Key Lab Robot & Intelligent Technol Changzhou 213022 Peoples R China Hohai Univ Jiangsu Key Lab Special Robots Changzhou 213022 Peoples R China Hohai Univ Coll IoT Engn Changzhou 213022 Peoples R China

To investigate the effects of muscle fatigue on bioinspired robot learning quality in teaching by demonstration (TbD) tasks, in this work, we propose to first identify the emerging muscle fatigue phenomenon of the human demonstrator by analyzing his/her surface Electromyography (sEMG) recordings and then guide the robot learning curve with this knowledge in mind. The time-varying amplitude and frequency sequences determining the subband sEMG signals have been estimated and their dominant values over short time intervals have been explored as fatigue-indicating features. These features are found carrying muscle fatigue cues of the human demonstrator in the course of robot manipulation. In robot learning tasks requiring multiple demonstrations, the fatiguing status of human demonstrator can be acquired by tracking the changes of the proposed features over time. In order to model data from multiple demonstrations, Gaussian mixture models (GMMs) have been employed. According to the identified muscle fatigue factor, a weight has been assigned to each of the demonstration trials in training stage, which is therefore termed as weighted GMMs (W-GMMs) algorithm. Six groups of data with various fatiguing status, as well as their corresponding weights, are taken as input data to get the adapted W-GMMs parameters. After that, Gaussian mixture regression (GMR) algorithm has been applied to regenerate the movement trajectory for the robot. TbD experiments on Baxter robot with 30 human demonstration trials show that the robot can successfully accomplish the taught task with a generated trajectory much closer to that of the desirable condition where little fatigue exists.

关键词： Demonstrations

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Motion Planning for Omnidirectional Wheeled Mobile Robot by Potential Field Method

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JOURNAL OF ADVANCED TRANSPORTATION 2017年第1期2017卷 1-11页

作者： Li, Weihao Yang, Chenguang Jiang, Yiming Liu, Xiaofeng Su, Chun-Yi South China Univ Technol Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China Swansea Univ Zienkiewicz Ctr Computat Engn Swansea SA1 8EN W Glam Wales Hohai Univ Coll IoT Engn Nanjing Jiangsu Peoples R China Hohai Univ Jiangsu Key Lab Special Robots Nanjing Jiangsu Peoples R China Changzhou Key Lab Robot & Intelligent Technol Changzhou Peoples R China

In this paper, potential field method has been used to navigate a three omnidirectional wheels' mobile robot and to avoid obstacles. The potential field method is used to overcome the local minima problem and the goals nonreachable with obstacles nearby (GNRON) problem. For further consideration, model predictive control (MPC) has been used to incorporate motion constraints and make the velocity more realistic and flexible. The proposed method is employed based on the kinematic model and dynamics model of the mobile robot in this paper. To show the performance of proposed control scheme, simulation studies have been carried to perform the motion process of mobile robot in specific workplace.

关键词： Mobile robots

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Improving Video Segmentation by Fusing Depth Cues and the Visual Background Extractor (ViBe) Algorithm

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SENSORS 2017年第5期17卷 1177-1177页

作者： Zhou, Xiaoqin Liu, Xiaofeng Jiang, Aimin Yan, Bin Yang, Chenguang Hohai Univ Coll Comp & Informat Engn Nanjing 211100 Jiangsu Peoples R China Changzhou Key Lab Robot & Intelligent Technol Changzhou 213022 Peoples R China Hohai Univ Jiangsu Key Lab Special Robots Changzhou 213022 Peoples R China Hohai Univ Coll IoT Engn Changzhou 213022 Peoples R China Shandong Univ Sci & Technol Coll Elect Commun & Phys Qingdao 266590 Peoples R China Swansea Univ Zienkiewicz Ctr Computat Engn Swansea SA1 8EN W Glam Wales

Depth-sensing technology has led to broad applications of inexpensive depth cameras that can capture human motion and scenes in three-dimensional space. Background subtraction algorithms can be improved by fusing color and depth cues, thereby allowing many issues encountered in classical color segmentation to be solved. In this paper, we propose a new fusion method that combines depth and color information for foreground segmentation based on an advanced color-based algorithm. First, a background model and a depth model are developed. Then, based on these models, we propose a new updating strategy that can eliminate ghosting and black shadows almost completely. Extensive experiments have been performed to compare the proposed algorithm with other, conventional RGB-D (Red-Green-Blue and Depth) algorithms. The experimental results suggest that our method extracts foregrounds with higher effectiveness and efficiency.

关键词： object detection background subtraction video surveillance Kinect sensor fusion

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