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2018 Australian and New Zealand control Conference, ANZCC 2018

作者： Yang, Rongni Zheng, Wei Xing School of Control Science and Engineering Shandong University Jinan Shandong250061 China School of Computing Engineering and Mathematics Western Sydney University SydneyNSW2751 Australia

ISBN: (纸本)9781538666173

In this paper, the observer-based predictive control problem for networked control systems (NCSs) subject to the time-delay is investigated based on the event-triggered strategy. Initially, the output-based event-triggered mechanism is introduced in order to reduce the transmission times effectively in the capacity-limited communication network. Then, the system states are reconstructed from the output measurements by utilizing a popular Luenberger observer. Next, the model-based networked predictive control (NPC) scheme is developed to actively compensate for the communication delay. Moreover, based on analysis of the augmented system, sufficient conditions that guarantee the asymptotic stability of the system are obtained. Finally, a simulation example is given to demonstrate the effectiveness in the reduction of network utilization and compensation for communication delay of the proposed controller design method in NCSs. © 2018 IEEE.

关键词： Networked control systems

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3D Face Reconstruction System From A Single Photo Based On Regression Neural Network

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IFAC-PapersOnLine 2020年第5期53卷 71-76页

作者： Yatai Ji Keqiang Li Huaiyu Wu Gang Xiong Zhen Shen Xiuqin Shang Bangwen Xi The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Automation Tsinghua University Beijing 100084 China University of Chinese Academy of Sciences Beijing 100049 China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Donggguan 523808 China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China

3D human face modeling is one of the most popular research directions in the field of computer stereo vision. On the one hand, the complex physiological structure of human face as well as various expressions and attitude changes bring great challenges to three-dimensional modeling, which makes the modeling method of human face have high research value and reference significance. On the other hand, 3D face reconstruction has a broad application prospect, and the application demand attracts more researchers to invest in it. Based on the 3DMM and 3DDFA method, this paper utilizes regression neural network to realize end-to-end face reconstruction. After that, we build a visualization program with the training model to realize face modeling based on a single face image of any pose or expression. It’s a 3D face reconstruction system which has functions such as face alignment, face rotation and so on.

关键词： face reconstruct 3DMM 3DDFA regression network

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LAENet: Light-weight asymmetric encoder-decoder network for semantic segmentation

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Journal of Physics: Conference Series 2021年第1期1966卷

作者： Liangyi Hong Shukai Duan Lidan Wang Yongbin Pan College of Electronic and Information Engineering Southwest University Chongqing China Brain-inspired Computing & Intelligent Control of Chongqing Key Lab Chongqing China National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing China Chongqing Brain Science Collaborative Innovation Center Chongqing China College of Artificial Intelligence Southwest University Chongqing China

Encode-decoder structure is used in deep learning for real-time dense segmentation task. On account of the limitation of calculation burden on mobile devices, we present a light-weight asymmetric encoder-decoder network in this paper, namely LAENet, which quickly and efficiently accomplish the task of real-time semantic segmentation. We employ an asymmetric convolution and group convolution structure combined with dilated convolution and dense connectivity to reduce computation cost and model size, which can guarantee adequate receptive field and enhance the model learning ability in encoder. On the other hand, feature pyramid networks (FPN) structure combine attention mechanism and ECRE block are utilized in the decoder to strike a balance between the network complexity and segmentation performance. Our approach achieves only have 0.84M parameters, and is able to reach 66 FPS in a single GTX 1080Ti GPU. Experiments on Cityscapes datasets demonstrate that superior performance of LAENet is better than the existing segmentation network, in terms of speed and accuracy trade-off without any post-processing.

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Robot Simulation and Reinforcement Learning Training Platform Based on Distributed Architecture 1

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4th International Conference on Cognitive Systems and Information Processing, ICCSIP 2018

作者： Jiang, Yun-Liang Huang, Zeng-Qiang Cao, Jun-Jie Liu, Yong Ma, Xinqiang Huang, Yi School of Computer Science Hangzhou Dianzi University Hangzhou310018 China School of Information Engineering Huzhou University Huzhou313000 China Institute of Cyber Systems and Control Zhejiang University Hangzhou310027 China Institute of Intelligent Computing and Visualization Based on Big Data Chongqing University of Arts and Sciences Chongqing402160 China

ISBN: (数字)9789811379833

ISBN: (纸本)9789811379826

In recent years, reinforcement learning, which enables robots to learn previously missing abilities, plays an increasingly important role in robotics, such as learning hard-to-code behaviors or optimizing problems without an accepted closed solution. The main problem of RL in robotics is that it is expensive and takes a long time to learn and operate. Another problem: advanced robot simulators like Gazebo are inefficient and time-consuming. In order to cope with these problems, a hybrid computing platform based on traditional robot simulation architecture and distributed architecture (hereinafter referred to as RDTP) is proposed in this paper, which helps to save cost, shorten time and speed up simulation and training. Additionally, the platform is optimized to a certain extent in terms of ease of use and compatibility. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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Gate-defined quantum dots in Ge/SiGe quantum wells as a platform for spin qubits 236

Gate-defined quantum dots in Ge/SiGe quantum wells as a plat...

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Symposium on Semiconductors, Dielectrics, and Metals for Nanoelectronics 17 - 236th ECS Meeting

作者： Hardy, W.J. Su, Y.-H. Chuang, Y. Maurer, L.N. Brickson, M. Baczewski, A. Li, J.-Y. Lu, T.-M. Luhman, D.R. Sandia National Laboratories AlbuquerqueNM87123 United States Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Center for Computing Research Sandia National Laboratories AlbuquerqueNM87123 United States Center for Quantum Information and Control University of New Mexico AlbuquerqueNM87131 United States

ISBN: (纸本)9781607688754

In the field of semiconductor quantum dot spin qubits, there is growing interest in leveraging the unique properties of hole-carrier systems and their intrinsically strong spin-orbit coupling to engineer novel qubits. Recent advances in semiconductor heterostructure growth have made available high quality, undoped Ge/SiGe quantum wells, consisting of a pure strained Ge layer flanked by Ge-rich SiGe layers above and below. These quantum wells feature heavy hole carriers and a cubic Rashba-type spin-orbit interaction. Here, we describe progress toward realizing spin qubits in this platform, including development of multi-metal-layer gated device architectures, device tuning protocols, and charge-sensing capabilities. Iterative improvement of a three-layer metal gate architecture has significantly enhanced device performance over that achieved using an earlier single-layer gate design. We discuss ongoing, simulation-informed work to fine-tune the device geometry, as well as efforts toward a single-spin qubit demonstration. ©The Electrochemical Society

关键词： Semiconductor quantum dots

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Multi-objective Optimal Path Planning for Mobile Robots using State Space Cell Mapping

Multi-objective Optimal Path Planning for Mobile Robots usin...

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IEEE Colombian Conference on Automatic control (CCAC)

作者： E. Grisales-Ramírez M.F. Jaramillo-Morales G. Osorio J.B. Gómez-Mendoza Perception and Intelligent Control (PCI) National University of Colombia Faculty of Engineering and Architecture Manizales Colombia Soft and Hard Applied Computing (SHAC) National University of Colombia Faculty of Engineering and Architecture Manizales Colombia

Cell mapping is a promising approach in multiple objective optimization problems. By discretizing the open-loop dynamical system in both the state space and time, it is possible to reduce the mathematical complexity of the problem while introducing constraints in practical mobile robots. Here, we propose to perform the discretization of the controlled system (closed-loop). This can be done introducing an additional constraint in the model that can be interpreted as a zero-order hold (ZOH) on the control. Because of the structure of the optimal problem, it is necessary to release a degree of freedom. This is achieved by allowing nonuniform discretization of time. We study the problem of a particle on a bidimensional configuration space with obstacles, optimizing time, distance and control energy. We also present some numerical results in a case of study with a three wheeled omnidirectional mobile robot in a constrained C-space.

关键词： Mobile robots Trajectory Aerospace electronics Kinematics Wheels

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Burning Zone Temperature Estimation of Rotary Kiln Using Flame Image Analysis in Cement Plants

Burning Zone Temperature Estimation of Rotary Kiln Using Fla...

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2018 International CET Conference on control, Communication, and computing, IC4 2018

作者： Shankar, S.S. Thomas, Lancy Pratheesh, H. Suresh, K. Centre for Development of Advanced Computing Control and Instrumentation Group Thiruvananthapuram Kerala India College of Engineering Dept. of ECE Thiruvananthapuram Kerala India

ISBN: (纸本)9781538649664

In a cement plant, the most important and critical part is the rotary kiln which is a large cylinder with a length of about 60-65 meters and a diameter of around 4.5 meters. The kiln is rotated by a powerful electrical motor. The output of kiln is clinker which is in the form of mould like balls. If the output clinker is powdered or in liquid state, then it cannot be used in further processing and will be wasted. In the current scenario, the kiln output is visually observed and the Clinker quality is hourly measured in the Laboratory. In the kiln, raw materials undergo burning around a temperature range of 1200°C to 1400°C. The clinker has to be critically burnt to achieve a desired quality. Excess heating of the raw materials leads to the production of over burnt clinker which is not useful for cement production. Such a situation results in the inefficient operation of kiln by wasting the energy spent for heating the raw materials. This is to be avoided in the cement sintering process. Burning zone temperature directly determines the characteristics of the clinker. Presently, in most of the cement plants, burning zone temperature measurement is obtained using radiation pyrometers. This measurement indicates temperature information about a particular point in the burning zone which is inadequate for the optimized operation and control of the kiln. The work includes the design and development of Image processing-based Temperature estimation System for the burning zone of a Rotary kiln. © 2018 IEEE.

关键词： Image segmentation

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Disturbance Observer-based Subspace Predictive control of a Pressurized Water-type Nuclear Reactor

Disturbance Observer-based Subspace Predictive Control of a ...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Vineet Vajpayee Victor Becerra Nils Bausch Shohan Banerjee Jiamei Deng S. R. Shimjith A. John Arul School of Energy and Electronic Engineering University of Portsmouth Portsmouth United Kingdom School of Built Environment Engineering and Computing Leeds Beckett University Leeds United Kingdom Reactor Control System Design Section Bhabha Atomic Research Centre Mumbai India Homi Bhabha National Institute Mumbai India Probabilistic Safety Reactor Shielding and Nuclear Data Section Indira Gandhi Centre for Atomic Research Kalpakkam India

ISBN: (数字)9781728159539

ISBN: (纸本)9781728159546

This work presents a disturbance observer-based predictive control strategy using a subspace matrix structure. The aim is to improve the capability of classical predictive controllers in handling external disturbances. A subspace-based predictive controller is designed directly from measurements. Then, a disturbance observer is designed using subspace matrices to estimate the external disturbance. Both of the designs are integrated using a feed-forward plus feed-back strategy to form the proposed control strategy. The proposed scheme is tested with a simulated model of a pressurized water nuclear reactor. The effectiveness of the proposed technique is demonstrated for two different load-following operations. Further, a quantitative analysis is performed to analyse the control performance of the proposed approach.

关键词： Inductors Predictive control Uncertainty Mathematical model Power generation Disturbance observers Load modeling

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Mobility in MANET Using Robot: A Review 1st

Mobility in MANET Using Robot: A Review

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1st International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2018

作者： Muchtar, Farkhana Abdullah, Abdul Hanan Ahmmad, Siti Nor Zawani Kumar, Yugal Faculty of Computing Universiti Teknologi Malaysia SkudaiJohor81310 Malaysia School of Computer Sciences Universiti Sains Malaysia GelugorPenang11800 Malaysia Instrumentation and Control Engineering University Kuala Lumpur MITEC Persiaran Sinaran Ilmu Bandar Seri Alam MasaiJohor81750 Malaysia Department of Science and Engineering and Information Technology Jaypee University of Information Technology Waknaghat SolanHimachal Pradesh173234 India

ISBN: (纸本)9789811338038

Recently, MANET (Mobile Ad Hoc Network) researchers have shown increased interest towards using mobile robot technology for their testbed platforms. Despite the existence of articles that discuss the usage of mobile robot technology pertaining to MANET testbed from the perspective of MANET researcher, the discussion provided in the papers are rather lacklustre as it is not the sole purpose of those articles. Hence, this review aims to discuss MANET testbeds that were facilitated with mobile robot technology from previous undertaken researches. With the wealth of information provided in this paper, it is hoped that this paper will be the ultimate source of reference for other MANET researchers who need to choose the most suitable mobile robots with real mobility in their MANET testbeds. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Mobile robots

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From social interaction to ethical AI: A developmental roadmap 8

From social interaction to ethical AI: A developmental roadm...

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Joint 8th IEEE International Conference on Development and Learning and Epigenetic Robotics, ICDL-EpiRob 2018

作者： Rolf, Matthias Crook, Nigel Steil, Jochen School of Engineering Computing and Maths Oxford Brookes University United Kingdom Institute for Robotics and Process Control Technische Universität Braunschweig Germany

ISBN: (纸本)9781538661109

AI and robot ethics have recently gained a lot of attention because adaptive machines are increasingly involved in ethically sensitive scenarios and cause incidents of public outcry. Much of the debate has been focused on achieving highest moral standards in handling ethical dilemmas on which not even humans can agree, which indicates that the wrong questions are being asked. We suggest to address this ethics debate strictly through the lens of what behavior seems socially acceptable, rather than idealistically ethical. Learning such behavior puts the debate into the very heart of developmental robotics. This paper poses a roadmap of computational and experimental questions to address the development of socially acceptable machines. We emphasize the need for social reward mechanisms and learning architectures that integrate these while reaching beyond limitations of plain reinforcement-learning agents. We suggest to use the metaphor of 'needs' to bridge rewards and higher level abstractions such as goals for both communication and action generation in a social context. We then suggest a series of experimental questions and possible platforms and paradigms to guide future research in the area. © 2018 IEEE.

关键词： Reinforcement learning

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