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IEEE International Conference on Fuzzy systems

作者： Chen Li Hongbin Ma Chenguang Yang Menyin Fu School of Automation as well as State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781479920747

This paper describes our preliminary development of a virtual robot teleoperation platform based on hand gesture recognition using visual information. Hand gestures in images captured by a camera are recognised to control a virtual iCub. We employ two methods to realise the classification: Adaptive Neuro-fuzzy Inference systems (ANFIS) and Support Vector Machines (SVM). We realise the teleoperation of a virtual robot using iCubSimulator. The technique in the paper will enable us to teleoperate a physical robot in the future work. In addition, a video server is set up to monitor the real robot. By using the parallel system we are able to improve the robot's performance. Based on the techniques presented in this paper, the virtual iCub can perform the specified actions remotely in a natural manner.

关键词： Solid modeling Mathematical model MATLAB Robot kinematics Gesture recognition Fuzzy logic

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Improving Auction Mechanisms for Online Real-Time Bidding Advertising with a Two-stage Resale Model

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IFAC-PapersOnLine 2017年第1期50卷 13575-13580页

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Real Time Bidding (RTB), widely publicized as one of the most promising big-data-driven business models for online computational advertising, has the potential of effectively monetizing user clicks and impressions via two-stage auctions with resale. Demand side platforms (DSPs) play a key role as intermediators in this auction process. Typically, the first-stage auctions will be conducted separately in each DSP to determine one winning advertiser registered on it, and in the second-stage auction, each DSP submits a bid based on its winning advertiser's bid to the ad exchange platform (AdX). The highest-bid DSP wins the ad impression from AdX and resells it to its winning advertiser in pursuit of the intermediate fee. This two-stage resale auction is a critical component in maintaining the effectiveness and efficiency of RTB ecosystems. In this paper, we strive to identify and design potential improvements for this auction mechanism with the aim of enhancing the total revenue of both advertisers and DSPs. We also validated our proposed auction mechanisms using the computational experiment approach. The experimental results indicate that our proposed mechanisms can make both advertisers and DSPs better off. Our work represents the first step towards a new research area of optimal mechanism design for RTB auctions, and is expected to provide useful managerial insights in RTB market practice. © 2017

关键词： Sales Commerce Machine design Auction mechanisms Computational advertisings Computational experiment Critical component Demand side Effectiveness and efficiencies Optimal mechanism designs Real time

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Stochastic stability of evolutionary prisoner's dilemma

Stochastic stability of evolutionary prisoner's dilemma

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2018 Australian and New Zealand control Conference, ANZCC 2018

作者： Liang, Haili Zhou, Zhao Zhang, Fan Peng, Chen Wang, Yu-Long Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Mathematics Southeast University Nanjing China

ISBN: (纸本)9781538666173

In this paper, we study two-player evolutionary prisoner's dilemma on regular graphs and identify the stochastically stable equilibria for infinite populations. We consider four different update rules: Birth-death(BD), death-birth(DB), imitation(IM) and pairwise comparison(PC). With the same values of cost and benefit of cooperation, we show that there is a unique stochastically stable equilibrium for evolutionary prisoner's dilemma on regular graphs. If the benefit-to-cost ratio is larger than k + 2 (k is the degree of a regular graph), the networked game has a higher fraction of cooperators than that for a well-mixed population. Under certain conditions, the lower graph connectivity can lead to the emergence of more cooperators. Besides theoretical analysis, we demonstrate our results through numerical computations and simulations as well. © 2018 IEEE.

关键词： Stochastic systems

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Adaptive control of Discrete-time Nonlinear systems Using ITF-ORVFL

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IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 556-563页

作者： Xiaofei Zhang Hongbin Ma Wenchao Zuo Man Luo School of Automation Beijing Institute of TechnologyBeijing 100081 School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China School of Automation Beijing Institute of Technologyand also with the State Key Laboratory of Intelligent Control and Decision of Complex Systems(Beijing Institute of Technology)Beijing 100081China School of Automation Beijing Institute of TechnologyBeijing 100081and he is with Beijing Institute of Electronic System EngineeringBeijing 100854China School of Automation Beijing Institute of TechnologyBeijing 100081and she is with Ant GroupBeijing 310013China

Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly *** network structure in which contains the direct links between inputs and outputs is unique,and stability analysis and real-time performance are two difficulties of the control systems based on neural *** this paper,combining the advantages of RVFL and the ideas of online sequential extreme learning machine(OS-ELM)and initial-training-free online extreme learning machine(ITFOELM),a novel online learning algorithm which is named as initial-training-free online random vector functional link algo rithm(ITF-ORVFL)is investigated for training *** link vector of RVFL network can be analytically determined based on sequentially arriving data by ITF-ORVFL with a high learning speed,and the stability for nonlinear systems based on this learning algorithm is *** experiment results indicate that the proposed ITF-ORVFL is effective in coping with nonparametric uncertainty.

关键词： Adaptive control initial-training-free online learning algorithm random vector functional link networks

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Effective distributed algorithm for solving linear matrix equations

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Science China(Information Sciences) 2023年第8期66卷 265-266页

作者： Songsong CHENG Jinlong LEI Xianlin ZENG Yuan FAN Yiguang HONG Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Anhui University Department of Control Science and Engineering Tongji University Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Dear editor,Solving linear matrix equations is a basic and important problem in many fields such as the computation of generalized inverses of matrices and(generalized) Sylvester equations. Also, the linear algebraic ...

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Visual Explanation of Object Detectors via Saliency Maps 18

Visual Explanation of Object Detectors via Saliency Maps

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Xiao, Jin Liu, Wenrui Hu, Xiaoguang Jiang, Hao Wang, Weipeng Yahang, Li Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing China Beihang University Beijing China The Third Academy of Casic Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350312201

In recent years, rapid progress of deep learning has resulted in object detection algorithms based on deep neural networks nearly completely replacing traditional methods. This shift has led to significant improvements in both accuracy and speed of object detection. However, deep neural networks that support decision-making inobject detection are complex black boxes with hidden internal logic and operations. This lack of transparency results in deep learning models being unexplainable, which limits their practical deployment. In this paper, we analyze the current state and future trends of interpretable technology in object detection and propose an effective object detection interpretable algorithm. This algorithm aims to explain the underlying logic of AI decision-making and provide support for the high performance and credibility of object detection algorithms based on deep neural networks through quantitative evaluation indicators. © 2023 IEEE.

关键词： Object detection

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Multi-UAV Cooperative Target Tracking Strategy Based on Formation control

Multi-UAV Cooperative Target Tracking Strategy Based on Form...

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第三十八届中国控制会议

作者： Duo Wang Zhihong Peng Xiaojie Ju Tao Yu Xue Wang China Academy of Launch Vehicle Technology School of Automation Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology

In this paper we mainly studies the cooperative tracking issue of multi-UAV based on formation control. The theory and method of formation control are introduced in the paper to ensure the continuous and effective ground target tracking results. The tracking targets are regarded as the leader or the structural center of the formation. The multi-UAVs are considered as followers to form an unstable formation system. The formation stability can be maintained by constructing control law to ensure the continuous and effective tracking of intelligent targets by the multi-UAV. The formation control method based on the leader-follower system and the potential function are adopted to ensure the stability of formation consists of UAVs and the target, so that UAVs can keep tracking of the target. We prove the tracking strategy and the formation control results by MATLAB simulation.

关键词： Cooperative target tracking formation control leader-follower system potential function

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MC-NeRF: Multi-Camera Neural Radiance Fields for Multi-Camera Image Acquisition systems

arXiv

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arXiv 2023年

作者： Gao, Yu Su, Lutong Liang, Hao Yue, Yufeng Yang, Yi Fu, Mengyin School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

Neural Radiance Fields (NeRF) use multi-view images for 3D scene representation, demonstrating remarkable performance. As one of the primary sources of multi-view images, multi-camera systems encounter challenges such as varying intrinsic parameters and frequent pose changes. Most previous NeRF-based methods assume a unique camera and rarely consider multi-camera scenarios. Besides, some NeRF methods that can optimize intrinsic and extrinsic parameters still remain susceptible to suboptimal solutions when these parameters are poor initialized. In this paper, we propose MC-NeRF, a method that enables joint optimization of both intrinsic and extrinsic parameters alongside NeRF. The method also supports each image corresponding to independent camera parameters. First, we tackle coupling issue and the degenerate case that arise from the joint optimization between intrinsic and extrinsic parameters. Second, based on the proposed solutions, we introduce an efficient calibration image acquisition scheme for multi-camera systems, including the design of calibration object. Finally, we present an end-to-end network with training sequence that enables the estimation of intrinsic and extrinsic parameters, along with the rendering network. Furthermore, recognizing that most existing datasets are designed for a unique camera, we construct a real multi-camera image acquisition system and create a corresponding new dataset, which includes both simulated data and real-world captured images. Experiments confirm the effectiveness of our method when each image corresponds to different camera parameters. Specifically, we use multi-cameras, each with different intrinsic and extrinsic parameters in real-world system, to achieve 3D scene representation without providing initial poses. The Code and supplementary materials are available at https://***/MC-NeRF Copyright © 2023, The Authors. All rights reserved.

关键词： Parameter estimation

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Attitude Calculating for a New Strap-down Inertial Navigation system Based on Angular Accelerometers

Attitude Calculating for a New Strap-down Inertial Navigatio...

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IEEE International Conference on Information and Automation

作者： Meiling Wang Xin Zheng Tong Liu Tonglei Wang Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Beijing Institute of Automatic Control Equipment Beijing China

ISBN: (纸本)9781509041039

This paper introduces an attitude updating method based on a new structure of gyroscope-free inertial navigation system(GFINS), in which the angular accelerometers are used to take the place of gyroscopes. For this new structure of GFINS, a new mathematical model is developed to determine the general three-dimensional motion of body segments. The mathematical model is mainly based on the direction cosine matrix. A second-order differential equation which is represented by angular acceleration should be calculated to solve this problem using the fourth order Runge-Kutta method combining with the interpolation method. Furthermore, the final result of this approach is shown by applying the mathematical model to some simulation data generated by the trajectory generator. The simulation results indicate that the mathematical model has a good performance.

关键词： angular accelerometer attitude updating direction cosine matrix GFINS

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A review of cooperative path planning of an unmanned aerial vehicle group

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Frontiers of Information Technology & Electronic Engineering 2020年第12期21卷 1671-1694页

作者： Hao ZHANG Bin XIN Li-hua DOU Jie CHEN Kaoru HIROTA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081China Department of Computational Intelligence and Systems Science Tokyo Institute of TechnologyTokyo 1528550Japan

As a cutting-edge branch of unmanned aerial vehicle(UAV)technology,the cooperation of a group of UAVs has attracted increasing attention from both civil and military sectors,due to its remarkable merits in functionality and flexibility for accomplishing complex extensive tasks,e.g.,search and rescue,fire-fighting,reconnaissance,and *** path planning(CPP)is a key problem for a UAV group in executing tasks *** this paper,an attempt is made to perform a comprehensive review of the research on CPP for UAV ***,a generalized optimization framework of CPP problems is proposed from the viewpoint of three key elements,i.e.,task,UAV group,and environment,as a basis for a comprehensive classification of different types of CPP *** following the proposed framework,a taxonomy for the classification of existing CPP problems is proposed to describe different kinds of CPPs in a unified ***,a review and a statistical analysis are presented based on the taxonomy,emphasizing the coordinative elements in the existing CPP *** addition,a collection of challenging CPP problems are provided to highlight future research directions.

关键词： Unmanned aerial vehicle group Cooperation Path planning Optimization problem

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