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Movement control and Attitude Adjustment of Climbing Robot on Flexible Surfaces

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2018年第3期65卷 2618-2628页

作者： Wu, Xinyu Liu, Jia Zhou, Yimin Lv, Qin Hu, Chaofang CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems and 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-Synergy Systems and 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-Synergy Systems and 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-Synergy Systems and Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Electrical and Information Engineering Tianjin University Tianjin China

In this paper, a series of control algorithms have been designed for the climbing cloth robot, "Clothbot" to climb vertically. The developed algorithm consists of three parts: a sliding mode control with integral action (SMC with integral action), a linear quadratic regulator, and dead reckoning for semi-autonomous navigation. First, the SMC with integral action is developed for high-precision position tracking and speed tracking of the permanent magnet direct current (PMDC) motor installed on the robot. The error between the expected velocity and the actual velocity of the PMDC motor is adopted to design the sliding surface. In order to compensate the fluctuation of the load torque due to the varied friction during climbing, an observer is formulated to estimate the load torque in real-time. Second, the LQR is employed for attitude adjustment by an active torque so as to prevent the robot from falling or being jammed during the movement. Third, due to the onboard-limited energy, the robot is just equippedwith semi-autonomous navigation named dead reckoning carrying on primary localization and primary path planning. Experiments are performed to verify the efficacy of the proposed control algorithms.

关键词： Climbing robot flexible surface linear quadratic regulator load observer sliding mode control with integral action

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Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surface Vehicle in Marine Environment

Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surf...

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Information Technology,Big Data and Artificial intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Xianzhi Qi Wenxing Fu Pei An Bingli Wu Jie Ma National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781728152240

ISBN: (纸本)9781728152257

Point cloud preprocessing is still a challenging task in the marine environment, for it is difficult to filter out non-obstacle points while avoiding damage to the obstacle completeness. In this paper, we propose a novel data preprocessing method on 3D LiDAR data for the unmanned surface vehicle in the marine environment. It consists of two tasks: outlier removal and wake filtering. As the spatial resolution of LiDAR changes with distance, we exploit distance normalization on statistical outlier filter for robust outlier removal. Considering the gradient difference between wave wake and obstacle surface near the water, we define and calculate the vertical state of point cloud on the range image to obtain the pre-filtering point set, and then use the RANSAC method to filter out the wake points. Experiments on real data has demonstrated the effectiveness of the proposed algorithm both in terms of feasibility and accuracy.

关键词： Three-dimensional displays Laser radar Filtering Filtering algorithms Spatial resolution Task analysis Measurement by laser beam

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Nb-embedded Janus WSSe monolayer as a resistive or Schottky gas sensor upon CO, HCHO and C2H3Cl in dry transformers: a first-principles investigation

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Physics Letters, Section A: General, Atomic and Solid State Physics 2025年 553卷

作者： He, Dan Li, Guangming Cao, Wen Cui, Hao Key Laboratory of Testing Technology for Manufacturing Process Southwest University of Science and Technology Mianyang621010 China Intelligent Operation for New Energy Based Power System Qinghai University Xining810016 China School of Information and Control Engineering Southwest University of Science and Technology Mianyang621010 China College of Artificial Intelligence Southwest University Chongqing400715 China

The inevitable insulation defects in dry transformers lead to the decomposition of epoxy resin into CO, HCHO, and C₂H₃Cl. To assess the operational status of such electrical equipment, this study proposes a Nb-embedded Janus WSSe (Nb-WSSe) monolayer on basis of first-principles theory as an outstanding material for typical gas detection. It is found that Nb-WSSe monolayer shows chemisorption towards three gas molecules, with largely tuned electronic property. The charge density difference, band structure, density of states and work function of the gas adsorbed systems are well-analyzed, and the sensing mechanism of Nb-WSSe monolayer for exploration of the resistive and Schottky gas sensors are uncovered. The findings manifest the favorable sensitivity and selectively of Nb-WSSe monolayer for detection of three gas *** findings presented in this study hold significant value, as they possess the potential to catalyze Janus TMDCs-based novel gas sensing candidates for use within the realm of electrical engineering. © 2025 Elsevier B.V.

关键词： Gas detectors

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The big data analysis of rail equipment accidents based on the maximal information coefficient

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Journal of Transportation Safety and Security 2020年第7期12卷 959-976页

作者： Shao, Fubo Yang, Shuguo Sun, Bangcheng Jia, Limin Dong, Yulin Wang, Dong School of Mathematics and Physics Qingdao University of Science and Technology Qingdao China Institute of Artificial Intelligence and Control Qingdao University of Science and Technology Qingdao China The Post-Doctor Station of the CRRC Corporation Limited Beijing China CRRC Academy Co. Ltd Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China College of Mathematics and Systems Science Shandong University of Science and Technology Qingdao China Institute of Transportation System Science and Engineering Beijing Jiaotong University Beijing China

With more electrical and electronic equipment applied into the railway system, much more data can be collected and then the big data era of railway is coming. By employing the maximal information coefficient (MIC), the big data analysis of rail equipment accidents is studied to investigate the effect of the updating of rail equipment. The rail equipment accident data set of 25 years (from 1990 to 2014) is separated into three subsets corresponding to the period of the occurrence time of accidents. For every subset, the contributing factors to accident damage, to accident severity, and to accident cause are analyzed, respectively. The results show that the variation trend of the number of rail equipment accidents is more consistent with the variety of railroad service miles rather than carloads. And the factor of highway-rail grade crossings is an important one which accords with the facts. However, a seemingly surprising result is found that there will be more contributing factors to accident severity and to accident causes with more equipment applied into the railway system as time goes on. © 2019, © 2019 Taylor & Francis Group, LLC and The University of Tennessee.

关键词： Big data rail equipment accident temporal analysis the maximal information coefficient

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A New Anomaly Detector of Flare Pilot Based on Siamese Network

A New Anomaly Detector of Flare Pilot Based on Siamese Netwo...

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Chinese Automation Congress (CAC)

作者： Xiaotian Xie Ke Gu Junfei Qiao Faculty of Information Technology Beijing University of Technology Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China Beijing Artificial Intelligence Institute Beijing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

The flare pilot is the key to ensure that the flare system is ignited at any time. At present, domestic and foreign companies mainly use thermocouples, flame ionization detectors and other sensors to detect the working condition of the flare pilot. These electronic components have the hysteretic and vulnerable problems due to extreme heat, thermal shock and vibration, which may well further lead to the failure to ignite the flare gas with flare pilot in time and cause production accidents. In view of the above problems, this paper proposes an anomaly detector of flare pilot based on deep learning technology. First of all, we made an anomaly detection database for flare pilot, which was shot in a domestic petrochemical company. Then, we designed a specific siamese network based on the triplet loss function for learning the similarity between the samples, in order to apply to the curing scene of the flare pilot. Finally, it is determined whether the flare pilot is abnormal according to the similarity between the input picture and the positive and negative samples. Experimental results demonstrate that the proposed method can be effectively used for the anomaly detection of flare pilot.

关键词： Databases Anomaly detection Petrochemicals Feature extraction Employee welfare Detectors Combustion

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The Performance Evaluation of SSVEP-BCI Actuated Wheelchair with Parameter Setting of Time-Window Length and Stimulation Layout

The Performance Evaluation of SSVEP-BCI Actuated Wheelchair ...

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Workshop on Metrology for Industry 4.0 and IoT

作者： Jun Xie Xiaojun Wu Peng Fang Guanglin Li Guozhi Cao Tao Xue Science and Technology on Electrooptic Control Laboratory Luoyang China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology & Shenzhen Engineering Laboratory of Neural Rehabilitation Shenzhen China School of Mechanical Engineering Xi'an Jiaotong University Xi'an China

ISBN: (数字)9781728148922

ISBN: (纸本)9781728148939

Due to the advantages of prominent brain responses, less training duration, and robustness to artifacts, steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) has been recently applied to intelligent wheelchair navigation. Recent researches mainly focused on the implementation of a specific recognition method to analyze the wheelchair navigation performance under fixed stimulation target number. The navigation performance evaluation under different recognition methods and different BCI target numbers is rarely compared. In this paper, the navigation performance comparison between different numbers of stimulation targets and different recognition methods was carried out. The multichannel integrated GT 2 circ and canonical correlation analysis (CCA) recognition methods were used to compare the wheelchair navigation performance under different time-window (TW) lengths. And the 3-target and 4-target arrangement layouts were adopted to compare the navigation performance between the “No feedback” and the “Feedback” conditions. Experimental results showed that the GT 2 circ recognition method with TW length of 2 s would promote the navigation efficiency and different stimulation target number could be tailored for different wheelchair application purposes, which would bring tutorial instructions to the applicable navigation of the BCI-actuated wheelchair.

关键词： brain-computer interface (BCI) steady-state visual evoked potential (SSVEP) wheelchair navigation time-window (TW) length stimulation layout Performance Evaluation Wheelchair parameter setting navigation Navigation efficiency Brain-Computer Interfaces Recognition (Psychology) Stimuli layouts

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Camouflaged Object Detection via Context-aware Cross-level Fusion

arXiv

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arXiv 2022年

作者： Chen, Geng Liu, Si-Jie Sun, Yu-Jia Ji, Ge-Peng Wu, Ya-Feng Zhou, Tao Northwestern Polytechnical University Xi’an710072 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering China Data Processing Center School of Power and Energy China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China School of Computer Science Inner Mongolia University Hohhot010021 China Artificial Intelligence Institute School of Computer Science Wuhan University Wuhan430072 China

Camouflaged object detection (COD) aims to identify the objects that conceal themselves in natural scenes. Accurate COD suffers from a number of challenges associated with low boundary contrast and the large variation of object appearances, e.g., object size and shape. To address these challenges, we propose a novel Context-aware Cross-level Fusion Network (C2F-Net), which fuses context-aware cross-level features for accurately identifying camouflaged objects. Specifically, we compute informative attention coefficients from multi-level features with our Attention-induced Cross-level Fusion Module (ACFM), which further integrates the features under the guidance of attention coefficients. We then propose a Dual-branch Global Context Module (DGCM) to refine the fused features for informative feature representations by exploiting rich global context information. Multiple ACFMs and DGCMs are integrated in a cascaded manner for generating a coarse prediction from high-level features. The coarse prediction acts as an attention map to refine the low-level features before passing them to our Camouflage Inference Module (CIM) to generate the final prediction. We perform extensive experiments on three widely used benchmark datasets and compare C2F-Net with state-of-the-art (SOTA) models. The results show that C2F-Net is an effective COD model and outperforms SOTA models remarkably. Further, an evaluation on polyp segmentation datasets demonstrates the promising potentials of our C2F-Net in COD downstream applications. Our code is publicly available at: https://***/Ben57882/C2FNet-TSCVT. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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An active fault-tolerant control strategy of aircraft engines based on multi-model predictive control

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International Journal of Turbo and Jet Engines 2020年第0期

作者： Du, Xian Ma, Yan-Hua School of Control Science and Engineering Dalian University of Technology Dalian China Jiangsu Province Key Laboratory of Aerospace Power System Nanjing China School of Microelectronics Dalian University of Technology Dalian China DUT Artificial Intelligence Institute Dalian China

In order to mitigate or even eliminate the adverse effects caused by typical components faults of aircraft engines, an active fault-tolerant strategy based on multi-model predictive control is proposed, which consists of a pre-established multi-model library, a judgement module, and corresponding predictive controllers with smooth transition switching logic. Multiple dynamic nonlinear or linear models are firstly established by means of system identification methods, based on the component-level nonlinear engine model or historical data in faults cases. The judgement module is utilized to online compare the engine measured outputs with that of all models in the pattern library and select the best matched dynamic model on the basis of outputs error quadratic performance index, thus determining the most appropriate predictive controller for the next control sample period. When a certain fault occurs, the fault model in the library could be identified and fault-model based predictive controller is activated. Finally, two kinds of pre-considered high-pressure compressor and high-pressure turbine component-level faults are taken as an example to design the active fault-tolerant controller. Simulation results show that the judgement module owns the ability to sense the fault and gives smooth switching signal to the suitable predictive controller, verifying the effectiveness of the proposed technique. © 2020 Walter de Gruyter GmbH, Berlin/Boston 2020.

关键词： Model predictive control

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On PID control for synchronization of complex dynamical network with delayed nodes

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Science China(Technological Sciences) 2019年第8期62卷 1412-1422页

作者： GU HaiBo Lv JinHu LIN ZongLi Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence Beihang University Beijing 100083 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904-4743 USA

Over the past two decades, synchronization, as an interesting collective behavior of complex dynamical networks, has been attracting much attention. To reveal and analyze the inherent mechanism of synchronization in complex dynamical networks with time delays in nodes, this paper attempts to use PD and PI control protocols to achieve synchronization. Based on a classical network model, we investigate the PD and PI control for synchronization of complex dynamical networks with delayed nodes and obtain some sufficient conditions. By using Lyapunov functions and appropriate state transformations, we prove that global synchronization can be achieved via the above control protocols. Finally, some simulation examples are illustrated to validate the effectiveness of the proposed theoretical results.

关键词： synchronization PID control complex dynamical network networked control system delayed node

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A Quantifiable Muscle Fatigue Method Based on sEMG during Dynamic Contractions for Lower Limb Exoskeleton

A Quantifiable Muscle Fatigue Method Based on sEMG during Dy...

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

作者： Shengcai Duan Can Wang Yuxiao Li Lufeng Zhang Ye Yuan 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-Synergy Systems Shenzhen Institutes of Advanced Technology University of Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China The Chinese University of Hong Kong

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

Advanced interactive methods between users and lower-limb exoskeletons are gradually drawing attention. Muscle fatigue is regarded as a significant contributory factor in muscle injuries and low work efficiency which is harmful to human-robot interactions. The detection and quantification of muscle fatigue during dynamic contractions remain as a challenging research. In this research, we introduce a novel method called Wavelet Packet Energy Entropy (WPEE) to quantify the muscle fatigue based on sEMG during dynamic contractions. Fatigue experiments and exoskeleton experiments are executed and three healthy subjects complete these experiments. sEMG signals from six muscles of arms are selected and analyzed. The results derived from fatigue experiments validate that the introduced method is better at quantifying the muscle fatigue compared with traditional method mean power frequency (MNF). WPEE is applied in exoskeleton experiments to investigate the arms' muscle fatigue under three conditions. The quantitative results detailly express the user's muscle fatigue condition and fatigue trends when the user is using an exoskeleton with crutches. Considering the muscle fatigue will contribute to ergonomic design and high-quality interactive control of exoskeleton.

关键词： Ergonomics Exoskeletons Muscles Fatigue Market research Wavelet packets Entropy

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