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arXiv 2021年

作者： Wang, Guangming Zhong, Jiquan Zhao, Shijie Wu, Wenhua Liu, Zhe Wang, Hesheng Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing 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 Department of Engineering Mechanics Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Technology University of Cambridge CambridgeCB2 1TN United Kingdom

Depth and ego-motion estimations are essential for the localization and navigation of autonomous robots and autonomous driving. Recent studies make it possible to learn the per-pixel depth and ego-motion from the unlabeled monocular video. A novel unsupervised training framework is proposed with 3D hierarchical refinement and augmentation using explicit 3D geometry. In this framework, the depth and pose estimations are hierarchically and mutually coupled to refine the estimated pose layer by layer. The intermediate view image is proposed and synthesized by warping the pixels in an image with the estimated depth and coarse pose. Then, the residual pose transformation can be estimated from the new view image and the image of the adjacent frame to refine the coarse pose. The iterative refinement is implemented in a differentiable manner in this paper, making the whole framework optimized uniformly. Meanwhile, a new image augmentation method is proposed for the pose estimation by synthesizing a new view image, which creatively augments the pose in 3D space but gets a new augmented 2D image. The experiments on KITTI demonstrate that our depth estimation achieves state-of-the-art performance and even surpasses recent approaches that utilize other auxiliary tasks. Our visual odometry outperforms all recent unsupervised monocular learning-based methods and achieves competitive performance to the geometry-based method, ORB-SLAM2 with back-end optimization. Copyright © 2021, The Authors. All rights reserved.

关键词： Robots

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Self-Tuning Clamping Force control with Optimal Trajectory Tracking for Autonomous Pipe Inspection Robots

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Journal of Pipeline science and Engineering 2025年

作者： Guoxin Sun Longfei Xia Xinpeng Du Qihui Yu Jianlong Zhang Ripeng Qin School of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia Autonomous Region 014010 China Inner Mongolia Engineering Technology Research Center of Mechatronics System Intelligent Diagnosis & Control Engineering 014010 China Inner Mongolia Ming yang North Smart Energy Research and Development Center Co LTD

To address the inability of existing external pipe-climbing robots to adaptively regulate clamping force during operation, a novel robot was developed. To enable automatic clamping in response to varying pipeline conditions, an adaptive clamping force control method based on optimal velocity trajectory tracking is proposed. This approach achieves adaptive clamping force regulation through indirect speed control. First, the target clamping force is calculated according to pipeline conditions and is then translated into a target rotational speed via optimal velocity trajectory planning. The motor then accurately tracks this speed signal, thereby ensuring precise control of the clamping force. Experimental results of the robot prototype demonstrate that the proposed algorithm maintains a clamping force control error of less than 5.0% across pipelines with different diameters, inclinations, and surface roughness—outperforming traditional PID control and ensuring stable operation under varying conditions of angle, diameter, and friction.

关键词： External pipe-crawling robot Adaptive clamping Optimal speed curve Tracking control

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Non-reciprocity of energy transfer derived from cubic stiffness-induced nonlinear phenomena

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Results in Physics 2025年 73卷

作者： Kong, Na Sun, Min Chen, Jianen Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin 300384 China School of Science Tianjin Chengjian University Tianjin 300384 China

Introducing purely nonlinear elastic elements can induce rich dynamic behaviors, such as bifurcations, jumps and isolated resonance curves, to linear systems. Therefore, these elements are suitable for constructing strong non-reciprocity of vibration energy transfer. First, the energy transfer along reciprocal directions in a three-degree-of-freedom system is investigated, where three oscillators are connected by cubic springs. The semi-analytical solutions of the system are obtained using the complexification-averaging method and the least squares method. The results are compared against numerical solutions obtained by the Runge-Kutta method. The excitation amplitude range that produces strong non-reciprocity of vibration energy is analyzed. The jump phenomenon under combined excitation is investigated, and a trigger method for constructing non-reciprocity using an impulse is proposed. Then, an oscillator chain with cubic stiffness and scaling parameters is embedded into a multi-degree-of-freedom linear oscillator system to further explore the effect of cubic stiffness. Energy transfer along two directions is compared by exciting the leftmost oscillator and the rightmost oscillator. Moreover, the trigger effect of the impulse on non-reciprocity is demonstrated. The results show significant differences in vibration energy transfer within three distinct frequency bands. The critical points between reciprocal and non-reciprocal states are obtained, and the three stages of reciprocity related to excitation amplitude are analyzed. Lastly, the modulation effect of the cubic stiffness on non-reciprocity is conducted by comparing the energy of the output oscillator. © 2025 The Authors

关键词： Cubic stiffness Energy transfer Jump phenomenon Non-reciprocity

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Exact Differentiator with Lipschitz Continuous Output and Optimal Worst-Case Accuracy Under Bounded Noise

Exact Differentiator with Lipschitz Continuous Output and Op...

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IEEE Conference on Decision and control

作者： Rodrigo Aldana-López Richard Seeber Hernan Haimovich David Gómez-Gutiérrez Department of Computer Science and Systems Engineering University of Zaragoza Zaragoza Spain Christian Doppler Laboratory for Model Based Control of Complex Test Bed Systems Institute of Automation and Control Graz University of Technology Graz Austria Centro Internacional Franco-Argentino de Ciencias de la Información y de Sistemas (CIFASIS) CONICET-UNR Rosario Argentina Intel Tecnología de México Intel Labs Intelligent Systems Research Lab Jalisco Mexico Tecnológico Nacional de México Instituto Tecnológico José Mario Molina Pasquel y Henríquez Unidad Académica Zapopan Jalisco Mexico

The online differentiation of a signal contaminated with bounded noise is addressed. A differentiator is developed that generates a Lipschitz continuous output, is exact in the absence of noise, and provides the optimal worst-case accuracy among all possible exact differentiators when noise is present. This combination of features is not shared by any previously existing differentiator. Tuning of the developed differentiator is very simple, requiring only the knowledge of a bound for the second-order derivative of the signal. The approach consists in regularizing the possibly highly noisy output of a recently introduced linear adaptive robust exact differentiator and feeding it to a first-order sliding-mode filter designed to maintain optimal accuracy. The proposed regularization and filtering of this output allows trading the speed with which exactness is obtained for the feature of a Lipschitz continuous, hence less noisy, output. An illustrative example is provided to highlight the features of the developed differentiator.

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An Iterative Closest Points Optimization Algorithm for Localization of Mecanum-wheeled Robots

An Iterative Closest Points Optimization Algorithm for Local...

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第三十八届中国控制会议

作者： Ning Hao Rui Xing Qi Zhao Fenghua He Hang Zhang Harbin Institute of Technology Complex System Control and Intelligent Agent Cooperation Laboratory

Over the last years, optimization based estimation methods have been applied with great success to a variety of state estimation problems. In this paper, we propose an optimization algorithm to solve the localization problem of Mecanumwheeled robots in a structured environment based on combination of odometer and laser lidar. First, provide the configuration of the mobile robot and the expression of localization problem based on probability form. Secondly, the optimization cost function is derived from the perspective of maximum posterior estimation. And then an iterative closest points optimization algorithm is proposed to address the combination optimization problem. Finally, simulation experiments are designed and implemented to validate the proposed algorithm.

关键词： localization state estimation iterative closest points optimization Mecanum-wheeled robot

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一种改进的纯组分物性预测机器学习模型（英文）

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Engineering 2024年第8期 61-73页

作者：曹欣羽贡铭 Anjan Tula 陈曦 Rafiqul Gani Venkat Venkatasubramanian State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Department of Physics Bard College at Simon's Rock PSE for SPEED Company Sustainable Energy and Environment Thrust The Hong Kong University of Science and Technology (Guangzhou) Department of Applied Sustainability Széchenyi István University Complex Resilient Intelligent Systems Laboratory Department of Chemical Engineering Columbia University

Information on the physicochemical properties of chemical species is an important prerequisite when performing tasks such as process design and product design. However, the lack of extensive data and high experimental costs hinder the development of prediction techniques for these properties. Moreover,accuracy and predictive capabilities still limit the scope and applicability of most property estimation methods. This paper proposes a new Gaussian process-based modeling framework that aims to manage a discrete and high-dimensional input space related to molecular structure representation with the group-contribution approach. A warping function is used to map discrete input into a continuous domain in order to adjust the correlation between different compounds. Prior selection techniques, including prior elicitation and prior predictive checking, are also applied during the building procedure to provide the model with more information from previous research findings. The framework is assessed using datasets of varying sizes for 20 pure component properties. For 18 out of the 20 pure component properties,the new models are found to give improved accuracy and predictive power in comparison with other published models, with and without machine learning.

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An Improved Segmentation Method for Porous Transducer CT Images

An Improved Segmentation Method for Porous Transducer CT Ima...

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2019第十一届数字图像处理国际会议

作者： Meiling Wang Ruoyu Guo Ke Ning Li Ming Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision

The paper presents an improved image segmentation method with a straightforward workflow for porous transducer CT images,which can be used to establish porous transducer three-dimensional model and further study its *** distribution of CT images is firstly analyzed and Gaussian filtering is conducted to reduce divergence of CT *** improved fully convolutional neural network model based on U-Net,for which multi-channel images are set as network input,is trained using training *** proposed method improves pore connectivity of the segmentation *** of porosity and permeability relative errors as well as MIOU on test set shows that the proposed method is an effective and generic two-phase segmentation method for porous transducer CT images without need of adjusting any parameters.

关键词： Porous transducer image segmentation permeability pore connectivity fully convolutional neural network

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Parallel Building Process Management system

Parallel Building Process Management System

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Chinese Automation Congress (CAC)

作者： Sheng Liu Xisong Dong Gang Xiong Zhen Shen Bin Hu Xiaoyu Chen State Key Laboratory for Management and Control of Complex System Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Institution of Intelligent Manufacturing Qingdao Academy of Intelligent Industries Qingdao China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426480

With the development of industrialized building and intelligence technology, it becomes necessary and possible to realize building process intelligence management. In recent years, digital twins and parallel management get more and more attentions in academic research and industrial applications. This paper addresses how parallel building system performs intelligence management on industrialized building process. Firstly, actual building model and artificial building model are created according to actual building system. Then business driving engine and simulation engine drive actual building model and artificial building model, respectively. Participants receive and send messages by software interfaces. Business driving engine changes the status of actual building model and sends the changes to simulation engine. Simulation engine updates the status of artificial building model and runs artificial building model with various parameters. Then it sends the parameter with the best effect to business driving engine. Business driving engine sends recommendations to participants according to the best parameter. Thus, building process intelligence management is achieved.

关键词： Automation Digital twin Buildings User interfaces Software Engines Business

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Adaptive Cruise control of Virtual Coupled High-Speed Trains

Adaptive Cruise Control of Virtual Coupled High-Speed Trains

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Chinese Automation Congress (CAC)

作者： Di Wang Yuan Cao Shuai Su State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Beijing China School of Electric and Information Engineering Beijing Jiaotong University Beijing China Frontiers Science Center for Smart High-Speed Railway System State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

ISBN: (纸本)9781665426480

The adaptive cruise formation control problem for multiple high-speed trains (MHSTs) with input, speed and minimum tracking distance constraints under virtual coupling (VC) is proposed in this paper. First, the dynamic equation of MHSTs is created based on the law of kinematics. The communication topology is modeled by graph theory. Next, the speed limit, minimum tracking distance with adjacent trains are dealt with by using the ideas of the potential function. The resistance and unknown disturbances are dealt with by using adaptive control. Then, a cruise control protocol for MHSTs to track the expected trajectory is designed. The Lyapunov theory is used to prove the system stability. Finally, numerical experiments are conducted, which illustrates that the control protocol is effective.

关键词： Adaptation models Protocols Mathematical models Stability analysis Graph theory Trajectory Numerical models

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A Practical and High-Performance Nitrogen Dioxide Gas Sensor that Can Be Rapidly Mass-Produced Based on Gallium Nitride Quantum Dots Film

SSRN

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SSRN 2022年

作者： Han, Dan Chen, Yi Li, Donghui Dong, Hailiang Xu, Bingshe Sang, Shengbo He, Xiuli Shanxi Key Laboratory of Micro Nano Sensors & Artificial Intelligence Perception College of Information and Computer Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Key Laboratory of Interface Science and Engineering in Advanced Materials Taiyuan University of Technology Ministry of Education Taiyuan030024 China State Key Laboratory of Transducer Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China Shanxi Research Institute of 6D Artificiat Intelligence Biomedical Science Taiyuan030024 China

Gallium nitride (GaN) has some challenges for gas sensing, such as high detection lower limit (LOD) or controlling the epitaxy of nanostructures. To address these issues, we exclusively designed a device to enhance the gas interaction capabilities of GaN quantum dots (QDs) film fabricated by metal-organic chemical vapor deposition (MOCVD). The GaN QDs film gas sensor exhibited a low LOD (5 ppb) to NO2 at room temperature (RT), which has much superior gas performance than other GaN-based sensors. The results manifest that many ultra-small QDs around 2 nm in diameter are stacked to form QDs of larger size, and confirm the existence of vacancies. The sensor displays a ultra-high electron mobility of 1237.37 cm2 V−1s−1, demonstrate that great shallow donor impurities in GaN QDs film that ionize easily at RT, which is greatly beneficial for gas sensing. The sensing mechanisms were analyzed based on its abundant active sites, ultrahigh carrier mobility, high surface energy and chemical activity, grain boundary barrier and good electrical conductivity. Moreover, the sensor processes high selectivity, repeatability, stability and reusability based on MOCVD technology which can realize precise control of structure, morphology and surface energy level, which is expected to achieve rapid industrialization. © 2022, The Authors. All rights reserved.

关键词： Gallium nitride

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