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Layers of Shared and Cooperative control, assistance and automation

IFAC-PapersOnLine 2016年第19期49卷 159-164页

作者： Pacaux-Lemoine, Marie-Pierre Flemisch, Frank Fraunhofer Institute for Communication Information Processing and Ergonomics FKIE Fraunhoferstrasse 20 Wachtberg53343 Germany Laboratory of Industrial and Human Automation control Mechanical engineering and Computer Science LAMIH CNRS UMR 8201 University of Valenciennes France

Over the last centuries we have experienced scientific, technological and societal progress that enabled the creation of intelligent assisted and automated machines with increasing abilities, and require a conscious distribution of roles and control between humans and machines. Machines can be more than either fully automated or manually controlled, but can work together with the human on different levels of assistance and automation in a hopefully beneficial cooperation. One way of cooperation is that the automation and the human have a shared control over a situation, e.g. a vehicle in an environment. The objective of this paper is to provide a common meta model of shared and cooperative assistance and automation. The meta models based on insight from the H(orse)-methaphor (Flemisch et al, 2003; Goodrich et al., 2006) and Human-Machine Cooperation principles (Hoc and Lemoine, 1998; Pacaux-Lemoine and Debernard, 2002; Pacaux-Lemoine, 2014), are presented and combined in order to propose a framework and criteria to design safe, efficient, ecological and attractive systems. Cooperation is presented from different points of view such as levels of activity (operational, tactical and strategic levels) (Lemoine et al, 1996) as well as the type of function shared between Human and machine (information gathering, information analysis, decision selection, action implementation) (Parasuraman et al., 2000). Examples will be provided in the aviation domain (e.g. Goodrich et. al 2012) and the automotive domain with the automation of driving (Hoeger et al, 2008; Flemisch et al., 2016; Tricot et al., 2004; Pacaux-Lemoine et al, 2004; Pacaux-Lemoine et al., 2015). © 2016

关键词： automation Man machine systems Attractive systems Automated machines Co operative control Human centered designs Human machine cooperation Information gathering Multi level systems Shared control

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Charged Particle Location Modeling Based Experiment Plan Acquisition Method

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Procedia computer Science 2017年 104卷 592-597页

作者： Normunds Kante Mykola Kryshchuk Jurijs Lavendels Riga Technical University Faculty of Computer Science and Information Technology Kaļķu street 1 Rīga LV – 1658 Latvia National Technical University of Ukraine (Kiev Polytechnic Institute) Department of Automation and Control in Technical Systems 37 Prospect Peremogy Kiev 03056 Ukraine

The method of obtaining the plan of experiments in multidimensional space is proposed. Our method is based on assumptions of uniform distribution of charged particles in infinite space. To receive the plan of experiments, the infinite multidimensional space is replaced with a hypercube whose surface models influence of infinite space. The software is developed and practical results, in two-dimensional space are acquired. There are no basic problems to carry out calculations in multidimensional space.

关键词： Experiment plan Charged particle interaction Latin hypercube

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Action recognition with joints-pooled 3D deep convolutional descriptors 25

Action recognition with joints-pooled 3D deep convolutional ...

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25th International Joint Conference on Artificial Intelligence, IJCAI 2016

作者： Cao, Congqi Yifan, Zhang Chunjie, Zhang Lu, Hanqing National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences China School of Computer and Control Engineering University of Chinese Academy of Sciences China

Torso joints can be considered as the landmarks of human body. An action consists of a series of body poses which are determined by the positions of the joints. With the rapid development of RGB-D camera technique and pose estimation research, the acquisition of the body joints has become much easier than before. Thus, we propose to incorporate joint positions with currently popular deep-learned features for action recognition. In this paper, we present a simple, yet effective method to aggregate convolutional activations of a 3D deep convolutional neural network (3D CNN) into discriminative descriptors based on joint positions. Two pooling schemes for mapping body joints into convolutional feature maps are discussed. The jointspooled 3D deep convolutional descriptors (JDDs) are more effective and robust than the original 3D CNN features and other competing features. We evaluate the proposed descriptors on recognizing both short actions and complex activities. Experimental results on real-world datasets show that our method generates promising results, outperforming state-of-the-art results significantly.

关键词： Deep neural networks

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Iterative Method for Solving a System of Linear Equations

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Procedia computer Science 2017年 104卷 133-137页

作者： Mykola Kryshchuk Jurijs Lavendels National Technical University of Ukraine (Kiev Polytechnic Institute) Department of Automation and Control in Technical Systems 37 Prospect Peremogy Kiev 03056 Ukraine Riga Technical University Faculty of Computer Science and Information Technology Kaļķu street 1 Rīga LV – 1658 Latvia

The systems of linear equations are a classic section of numerical methods which was already known BC. It reached its highest peak around 1600-1700 due to the public demand for solutions of technical and engineering tasks, nevertheless, it is still topical nowadays. This paper describes another iterative approach to solving linear systems, which is based in the multiple transfers of the solution proximity point towards the solution itself, simultaneously reducing the differences of all the system equations.

关键词： The systems of linear equations Iterative methods for solving systems of linear equations The requirements for the matrix of the equation system

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Learning robust and discriminative low-rank representations for face recognition with occlusion

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Pattern Recognition 2017年 66卷 129-143页

作者： Guangwei Gao Jian Yang Xiao-Yuan Jing Fumin Shen Wankou Yang Dong Yue Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China Jiangsu Engineering Laboratory of Big Data Analysis and Control for active distribution network Nanjing University of Posts and Telecommunications Nanjing China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control (Minjiang University) Fuzhou China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Automation Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Automation Southeast University Nanjing China

For robust face recognition tasks, we particularly focus on the ubiquitous scenarios where both training and testing images are corrupted due to occlusions. Previous low-rank based methods stacked each error image into a vector and then used L 1 or L 2 norm to measure the error matrix. However, in the stacking step, the structure information of the error image can be lost. Depart from the previous methods, in this paper, we propose a novel method by exploiting the low-rankness of both the data representation and each occlusion-induced error image simultaneously, by which the global structure of data together with the error images can be well captured. In order to learn more discriminative low-rank representations, we formulate our objective such that the learned representations are optimal for classification with the available supervised information and close to an ideal-code regularization term. With strong structure information preserving and discrimination capabilities, the learned robust and discriminative low-rank representation (RDLRR) works very well on face recognition problems, especially with face images corrupted by continuous occlusions. Together with a simple linear classifier, the proposed approach is shown to outperform several other state-of-the-art face recognition methods on databases with a variety of face variations.

关键词： Face recognition Low-rank matrix recovery Nuclear norm

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A hierarchical urban network control with integration of demand balance and traffic signal coordination

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IFAC-PapersOnLine 2016年第3期49卷 31-36页

作者： Zhou, Zhao Lin, Shu Xi, Yugeng Li, Dewei Zhang, Jun Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control Information Processing Ministry of Education of China Shanghai200240 China School of Computer and Control Engineering University of Chinese Academy of Science Beijing100049 China Joint Institute of UM-SJTU Shanghai Jiao Tong University Shanghai200240 China

This paper concerns the integration of demand balance control and traffic flow coordination control in a hierarchical framework for complex urban traffic networks. At the first level, a complex traffic network is first partitioned into several subnetworks. The traffic dynamics in each subnetwork is modeled by utilizing the concept of Macroscopic Fundamental Diagram (MFD), which relates the network-wide space-mean flow and the number of vehicles at the aggregated level. This model aims at designing a demand balance model predictive controller (MPC), which can improve the internal flow inside the subnetwork by regulating the input flows from outside. At the second level, based on a more detailed traffic flow model, the signal timings of all intersections for each subnetwork are determined by a flow coordination MPC controller, which aims at distributing the number of vehicles in each subnetwork as homogeneously as possible. The effectiveness of the proposed approach is investigated via simulation under different scenarios on a hypothetical urban traffic network, and the performance is compared with other control strategies. © 2016

关键词： Street traffic control

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Compressive phase retrieval via reweighted amplitude flow

arXiv

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arXiv 2017年

作者： Zhang, Liang Wang, Gang Giannakis, Georgios B. Chen, Jie Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

The problem of reconstructing a sparse signal vector from magnitude-only measurements (a.k.a., compressive phase retrieval), emerges naturally in diverse applications, but it is NP-hard in general. Building on recent advances in nonconvex optimization, this paper puts forth a new algorithm that is termed compressive reweighted amplitude flow and abbreviated as CRAF, for compressive phase retrieval. Specifically, CRAF operates in two stages. The first stage seeks a sparse initial guess via a new spectral procedure. In the second stage, CRAF implements a few hard thresholding based iterations using reweighted gradients. When there are sufficient measurements, CRAF provably recovers the underlying signal vector exactly with high probability under suitable conditions. Moreover, its sample complexity coincides with that of the state-of-the-art procedures. Finally, substantial simulated tests showcase remarkable performance of the new spectral initialization, as well as improved exact recovery relative to competing alternatives. Copyright © 2017, The Authors. All rights reserved.

关键词： Iterative methods

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Fault-tolerant control for deterministic discrete event systems with measurable state

Fault-tolerant control for deterministic discrete event syst...

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American control Conference

作者： Melanie Schuh Jan Lunze Institute of Automation and Computer Control Ruhr-Universitat Bochum Germany

ISBN: (纸本)9781467386838

A method for the fault-tolerant control of discrete event systems modeled by deterministic input/output (I/O) automata with measurable state is proposed. The scheme consists of a diagnostic unit and a reconfiguration unit in order to detect and identify the fault and to reconfigure the controller consisting of a trajectory planning unit and a controller automaton. During the reconfiguration of the controller, the trajectory to the desired final state is re-planned and the controller automaton is modified by removing and adding certain transitions. It is proved that in the proposed fault-tolerant control loop the faulty plant reaches the desired final state without any external intervention, if the control loop is recoverable.

关键词： Automata Fault tolerance Fault tolerant systems Trajectory Discrete-event systems Fault diagnosis Planning discrete event systems fault-tolerant control Automata Fault tolerant systems trajectory Fault tolerance Fault diagnosis terminal states controllers control ring DIAGNOSTIC INSTRUMENT Reconfiguration

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Fault-tolerant control of deterministic I/O automata using active diagnosis

Fault-tolerant control of deterministic I/O automata using a...

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European control Conference

作者： Melanie Schuh Jan Lunze the Institute of Automation and Computer Control Ruhr-Universitat Bochum Germany

ISBN: (纸本)9781509025923

A method for the fault-tolerant control of discrete event systems modeled by deterministic Input/Output automata is proposed with an emphasis on the fault diagnosis. When a fault is detected, the diagnostic unit generates a homing sequence as an input to the controller such that from the output of the plant the present fault and the current state of the faulty plant can be deduced. With this knowledge the controller is reconfigured. A condition for the recoverability of the control loop is stated and it is proved that in the proposed fault-tolerant control loop the faulty plant reaches the desired final state without any external intervention, if the control loop is recoverable.

关键词： Fault-tolerant control deterministic I/O automata active diagnosis

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12.2: A 3D Display Parallel System: Light Field Re-rendering and Depth Sense Optimization

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SID Symposium Digest of Technical Papers 2018年第S1期49卷

作者： Renjing Pei Kui Ma Feiyue Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences East Zhongguanchun Road No. 95 Haidian District Beijing School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing Parallel Optics Technology Innovation Center Qingdao Academy of Intelligent Industries Qingdao

The main benefit of 3D display over 2D display is the obvious ability to create a more lifelike character with high depth sense. However, the limitation of human eye's visual mechanism, unartful 3D scene structure design, or bad viewing condition always emerges poor depth perception experience or even physiological discomfort during the watching time, which is often sub-optimal for mass high-quality 3D display productions. To solve this problem, we propose a novel 3D display parallel system for depth sense optimization and it empirically guides how the light field should be re-rendered. Structurally, the parallel system consists of an artificial perception measurement system, a display evaluation model and a light field display rendering system, which includes the display calibration, scene capture, light field data processing and display. Particularly, the system can systematically analyze and model various factors affecting the depth sense which learned through the measurement system, like scene structure, objects’ speeds in 3D video and so on. And those sense factors can be personally modified or increased according to the viewer's demands or technical improvement. Moreover, the light field could be real-time re-rendered, based on some image processing technology, optical flow analysis and object segmentation (or tracking) (especially the one-shot video segmentation). Theory and algorithms are developed and experimental validation results show a superior performance.

关键词： 3D Display Parallel System Depth Sense Light Field Re-rendering 3D Video Processing One-shot Segmentation

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