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作者： He, Wei Voon Ee How, Bernard Ge, Shuzhi Sam Choo, Yoo Sang Department of Electrical and Computer Engineering Centre for Offshore Research and Engineering National University of Singapore Singapore 117576 Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore Institute of Intelligent Systems and Information Technology University of Electronic Science and Technology of China Chengdu 610054 China Department of Civil Engineering Centre for Offshore Research and Engineering National University of Singapore Singapore 117576 Singapore

ISBN: (纸本)9781424474264

In this paper, boundary control of a flexible marine riser with vessel dynamics is developed to reduce the riser's vibrations. To provide an accurate and concise representation of the riser's dynamic behavior, the distributed parameter model of the flexible marine riser with vessel dynamics is described by a partial differential equation (PDE) coupled with ordinary differential equations (ODEs) involving functions of space and time. Boundary control is developed at the top boundary of the riser based on Lyapunov's direct method to regulate the riser's vibrations. With the proposed boundary control, uniform boundedness is achieved. The boundary control is implementable with actual instrumentation since all the signals in the control can be measured by sensors or calculated by a backwards difference algorithm. Simulations are provided to illustrate the effectiveness of the proposed control. © 2010 AACC.

关键词： Dynamics

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Parallel matching-based estimation - a case study on three different hardware architectures

Parallel matching-based estimation - a case study on three d...

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IEEE Symposium on intelligent Vehicle

作者： Benjamin Ranft Timo Schoenwald Bernd Kitt Intelligent Systems and Production Engineering (ISPE) research division FZI Research Centre for Information Technology Germany Department of Measurement and Control Karlsruhe Institute of Technology Germany

Many advanced driver assistance systems (ADAS) and autonomous vehicles require 3D information available from (stereo) camera systems. The corresponding task of estimating disparity or optical flow is computationally demanding, so meeting real-time update rates at high image resolutions has proven to be challenging. Modern parallel hardware seems suitable for this task only if its processing power can be efficiently accessed by parallel software implementations. In this paper we present a case study comparing different hardware platforms by two variants of block matching-based estimation. These platforms include two x86-compatible multicore systems, a graphics processing unit (GPU) and a 64-core embedded design. We introduce relevant features of each architecture and describe their effects on the applied algorithms, parallelization approaches and implementations. Target platforms are evaluated concerning computational performance, energy efficiency and programmer productivity.

关键词： Graphics processing unit Instruction sets Pixel Hardware Cameras Optical imaging Estimation

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Soft Computing for intelligent Robotic systems 1

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丛书名： Studies in Fuzziness and Soft Computing

1000年

作者： Lakhmi C. Jain Toshio Fukuda

ISBN: (数字)9783790818826

ISBN: (纸本)9783662130032

research results using some of the most advanced soft computing techniques in intelligent robotic systems are presented. The main purpose of this book is to show how the power of soft computing techniques can be exploited in intelligent robotic systems. The main emphasis is on control system for a mobile robot, behavior arbitration for a mobile robot, reinforcement learning of a robot, manipulation of a robot, collision avoidance and automatic design of robots.;This book will be useful for application engineers, scientists and researchers who wish to use some of the most advanced soft computing techniques in robotics.

关键词： Artificial Intelligence IT in Business Complexity control, Robotics, Mechatronics engineering Economics, Organization, Logistics, Marketing

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Interactive wearable digital devices for blind and partially sighted people

Nature Reviews Electrical Engineering

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Nature Reviews Electrical engineering 2025年 1-15页

作者： Wenhao Xue ( Tianfang Zhang ( Xiaonan Dong ( Xuezhi Ma ( Heng Xu ( Jiaqing Zhao ( Yuan Ma ( Department of Mechanical Engineering and Research Institute for Intelligent Wearable Systems The Hong Kong Polytechnic University Hong Kong S.A.R China Department of Rehabilitation Medicine First Affiliated Hospital College of Medicine Zhejiang University Hangzhou China Technology Innovation Center Zhe Jiang Key Laboratory of Intelligent Rehabilitation and Translational Neuroelectronics Hangzhou China Life and Health Institute China Resources Research Institute of Science and Technology Company Ltd Hong Kong S.A.R. China School of Biomedical Sciences LKS Faculty of Medicine The University of Hong Kong Hong Kong S.A.R. China A*STAR Quantum Innovation Centre (Q. InC) Agency for Science Technology and Research Singapore Singapore Institute of Materials Research and Engineering Agency for Science Technology and Research Singapore Singapore Department of Haptic Intelligence CVTE Guangzhou Shiyuan Electronics Company Ltd Guangzhou China Institute of Nuclear and New Energy Technology Tsinghua University Beijing China Research Center for Green and Smart Manufacturing PolyU-Daya Bay Technology and Innovation Research Institute Huizhou China

Digital information has permeated all aspects of life, and diverse forms of information exert a profound influence on social interactions and cognitive perceptions. In contrast to the flourishing of digital interaction devices for sighted users, the needs of blind and partially sighted users for digital interaction devices have not been adequately addressed. Current assistive devices often cause frustration in blind and partially sighted users owing to the limited efficiency and reliability of information delivery and the high cognitive load associated with their use. The expected rise in the prevalence of blindness and visual impairment due to global population ageing drives an urgent need for assistive devices that can deliver information effectively and non-visually, and thereby overcome the challenges faced by this community. This Perspective presents three potential directions in assistive device design: multisensory learning and integration; gestural interaction control; and the synchronization of tactile feedback with large-scale visual language models. Future trends in assistive devices for use by blind and partially sighted people are also explored, focusing on metrics for text delivery efficiency and the enhancement of image content delivery. Such devices promise to greatly enrich the lives of blind and partially sighted individuals in the digital age.

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Cooperative Target-Surrounding control of Unmanned Surface Vessels Based on MADDPG 49

Cooperative Target-Surrounding Control of Unmanned Surface V...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Li, Taoman Zhu, Fei Gan, Zihan Zhou, Zexing Wang, Xiaotao Lu, Renzhi China Ship Scientific Research Center Wuxi214082 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China Wuhan University of Science and Technology Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan430081 China

ISBN: (纸本)9798350331820

This article proposes a multi-agent deep reinforce-ment learning algorithm to control a fleet of unmanned surface vessels (USVs) that encircle and capture sea targets. First, a simulation environment for USVs is established based on a dynamic model;two-dimensional control variables are used to control movements in three directions. Second, the multi-agent deep deterministic policy gradient (MADDPG) algorithm is employed to achieve intelligent control of the USVs, using a reward function based on certain prior knowledge. Finally, centralized training and decentralized execution are used to complete the offline learning of multiple agents, and continuous action decisions are made based on the observations of the USV sensors. Simulations demonstrate that the method can capture stationary moving sea targets with any number of multi-agents under disturbances, and exhibits strong robustness and practicality. © 2023 IEEE.

关键词： Reinforcement learning

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Development of a global road safety performance function using deep neural networks

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International Journal of Transportation Science and technology 2017年第3期6卷 159-173页

作者： Pan, Guangyuan Fu, Liping Thakali, Lalita Department of Civil & Environmental Engineering University of Waterloo Waterloo N2L 3G1 ON Canada Intelligent Transportation Systems Research Centre Wuhan University of Technology Mailbox 125 No. 1040 Heping Road Wuhan 430063 Hubei China

This paper explores the idea of applying a machine learning approach to develop a global road safety performance function (SFP) that can be used to predict the expected crash frequencies of different highways from different regions. A deep belief network (DBN) – one of the most popular deep learning models is introduced as an alternative to the traditional regression models for crash modelling. An extensive empirical study is conducted using three real world crash data sets covering six classes of highways as defined by location (urban vs. rural), number of lanes, access control, and region. The study involves a number of experiments aiming at addressing several critical questions pertaining to the relative performance of the DBN in terms of network structure, training method, data size, and generalization ability, as compared to the traditional regression models. The experimental results have shown that a DBN model could be trained with different crash datasets with prediction performance being at least comparable to that of the locally calibrated negative binomial (NB) model. © 2017

关键词： Collision model Deep learning Global model Road safety

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洋流干扰下无人船限制水域直线跟踪安全视距制导

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哈尔滨工程大学学报（英文版） 2023年第3期22卷 602-613页

作者：彭周华李建众韩冰古楠 School of Marine Electrical Engineering Dalian Maritime UniversityDalian 116026China Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships Dalian 116026China Shanghai Ship and Shipping Research Institute Co.Ltd. Shanghai 200135China National Engineering Research Center of Ship&Shipping Control System Shanghai 200135China

The collision-free straight-line following of an unmanned surface vehicle(USV)moving in a constrained water region subject to stationary and moving obstacles is addressed in this *** systems are normally subjected to surge velocity constraints,yaw rate constraints,and unknown ocean ***,a safety-certificated line-of-sight(LOS)guidance method is proposed to achieve a constrained straight-line following ***,an antidisturbance LOS guidance law is designed based on the LOS guidance scheme and an extended state ***,collision avoidance with waterway boundaries and stationary/moving obstacles is encoded in control barrier functions,utilizing which the safety constraints are transformed into input ***,safety-certificated guidance signals are obtained by solving a quadratic programming problem subject to input *** the proposed safety-certified LOS guidance method,the USV can accomplish a straight-line following task with guaranteed input-to-state *** results substantiate the efficacy of the proposed safety-certificated LOS guidance method for the straight-line following of USVs moving in a constrained water region subject to unknown ocean currents.

关键词： Line-of-sight guidance Constrained water region Unmanned surface vehicle control barrier function Extended state observer

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Design of an Experimental Framework for Testing and Evaluation of Autonomous ships Based on the Turing Test 7

Design of an Experimental Framework for Testing and Evaluati...

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7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023

作者： Yu, Yue Li, Shijie Liu, Jialun Hu, Xinjue Guan, Hongxu School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan China China State Shipbuilding Corporation Laboratory of Science and Technology on Marine Navigation and Control Tianjin China National Engineering Research Center for Water Transport Safety Wuhan China Wuhan University of Technology State Key Laboratory of Maritime Technology and Safety Wuhan China Wuhan University of Technology School of Transportation and Logistics Engineering Wuhan China Wuhan University of Technology Intelligent Transportation Systems Research Center Wuhan China Wuhan University of Technology School of Navigation Wuhan China

ISBN: (纸本)9798350308532

In recent years, there has been a significant growth in intelligent ship technology. As the automation, intelligence, and autonomous development of ships continue to advance, it becomes crucial to conduct extensive testing and verification to ensure the rationality, reliability, and integrity of their functions and performance. Developing a mature and efficient intelligent testing and evaluation system becomes a prerequisite for further advancement in intelligent ship technology. This paper proposes a method for designing an experimental framework for intelligent navigation testing of ships, utilizing the Turing test. The first step involves building the necessary hardware and software experimental platform based on the requirements of driving behavior. Additionally, standardized experimental steps are designed to align with the characteristics of the platform. Subsequently, an experimental data evaluation method is proposed, based on probabilistic statistics and considering different navigation scenarios and characteristics of navigation data. This method relies on the principles of the normal distribution law. Finally, a human-machine confrontation experimental framework is constructed, based on the Turing test principle. The effectiveness of this framework is verified by integrating the experimental platform and experimental parameters. The proposed experimental framework serves as a reference and provides theoretical support for intelligent ship navigation testing, with the aim of promoting the overall development of intelligent ships. © 2023 IEEE.

关键词： ships

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Predicting the Trajectories of Vessels Using Machine Learning

Predicting the Trajectories of Vessels Using Machine Learnin...

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International Conference on Cybernetics, Robotics and control (CRC)

作者： Xinglong Liu Wei He Jinguang Xie Xiumin Chu College of Physics and Electronic Information Engineering Minjiang University (MJU) Fujian Engineering Research Center of Safety Control for Ship Intelligent Navigation (MJU) Fuzhou P.R. China National Engineering Research Centre for Water Transport Safety (WTS) Wuhan University of Technology (WHUT) Wuhan P. R. China Fujian Engineering Research Center of Safety Control for Ship Intelligent Navigation (MJU) Fuzhou P.R. China

ISBN: (数字)9781728186245

ISBN: (纸本)9781728186252

Trajectory predicting plays an important role in port and shipping management. The Automatic Identification System (AIS) is conducive to ship navigation safety for it enables the navigation information exchanges between vessels and shore authorities. However, the AIS data get lost occasionally for the communication reliability reasons. Hence, it is necessary to predict the trajectory of vessels to enhance shipping management. In this study, an approach for predicting trajectories of vessels by utilizing historical AIS data was proposed. Firstly, an interpolation method was employed to regularize the AIS data. Accordingly, a historical AIS database composed of thousands of trajectories are created. Secondly, a method for querying similar trajectories from the historical AIS database was designed. With the similar trajectories, the lost track points can be predicted by a regression model named Least Squares Support Vector Machine (LSSVM). The minimum sum of mean square error (MSE) was treated as the optimization objective, and the Particle Swarm Optimization (PSO) was utilized to train the parameters of the regression model. In the end, the experimental results indicated that the proposed method is capable of accurately predicting the position of vessels.

关键词： Support vector machines Navigation Databases Trajectory Safety Artificial intelligence Robots

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Data-Driven Discovery of Stochastic Differential Equations

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engineering 2022年第10期17卷 244-252页

作者： Yasen Wang Huazhen Fang Junyang Jin Guijun Ma Xin He Xing Dai Zuogong Yue Cheng Cheng Hai-Tao Zhang Donglin Pu Dongrui Wu Ye Yuan Jorge Gonçalves Jürgen Kurths Han Ding School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Mechanical Engineering University of KansasLawrenceKS 66045USA HUST-Wuxi Research Institute Wuxi 214174China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Department of Plant Sciences University of CambridgeCambridge CB23EAUK Luxembourg Centre for Systems Biomedicine University of LuxembourgBelvaux 4367Luxembourg Department of Physics Humboldt University of BerlinBerlin 12489Germany Department of Complexity Science Potsdam Institute for Climate Impact ResearchPotsdam 14473Germany

Stochastic differential equations(SDEs)are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different *** identification of SDEs governing a system is often a challenge because of the inherent strong stochasticity of data and the complexity of the system’s *** practical utility of existing parametric approaches for identifying SDEs is usually limited by insufficient data *** study presents a novel framework for identifying SDEs by leveraging the sparse Bayesian learning(SBL)technique to search for a parsimonious,yet physically necessary representation from the space of candidate basis *** importantly,we use the analytical tractability of SBL to develop an efficient way to formulate the linear regression problem for the discovery of SDEs that requires considerably less time-series *** effectiveness of the proposed framework is demonstrated using real data on stock and oil prices,bearing variation,and wind speed,as well as simulated data on well-known stochastic dynamical systems,including the generalized Wiener process and Langevin *** framework aims to assist specialists in extracting stochastic mathematical models from random phenomena in the natural sciences,economics,and engineering fields for analysis,prediction,and decision making.

关键词： Data-driven method System identification Sparse Bayesian learning Stochastic differential equations Random phenomena

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