检索结果-南通市图书馆

A general methodology for mobility analysis of mechanisms based on constraint screw theory

在线全文

学校读者我要写书评

暂无评论

Science China(Technological Sciences) 2009年第5期52卷 1337-1347页

作者： Zhen Huang JingFang Liu DaXing Zeng robotics Research center Yanshan University Qinhuangdao 066004 China

It is well known that the traditional Grübler-Kutzbach formula fails to calculate the mobility of some classical mechanisms or many modern parallel robots,and this situation seriously hampers mechani-cal *** seek an efficient and universal method for mobility calculation has been a heated topic in the sphere of *** modified Grübler-Kutzbach criterion proposed by us achieved success in calculating the mobility of a lot of highly complicated mechanisms,especially the mobility of all recent parallel mechanisms listed by Gogu,and the Bennett mechanism known for its particular *** wide applications of the criterion,a systematic methodology has recently *** paper systematically presents the methodology based on the screw theory for the first time and ana-lyzes six representative puzzling *** addition,the methodology is convenient for judgment of the instantaneous or full-cycle mobility,and has become an effective and general method of great scientific value and practical *** the first half,this paper introduces the basic screw theory,then it presents the effective methodology formed within this *** second half of this paper presents how to apply the methodology by analyzing the mobility of several puzzling ***,this paper contrasts and analyzes some different methods and interprets the essential reason for validity of our methodology.

关键词： mobility analysis redundant constraint parallel mechanism

Mobility of the Myard 5R Linkage Involved in “Gogu Problem”

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Mechanical Engineering 2009年第3期22卷 325-330页

作者： LIU Jingfang HUANG Zhen LI Yanwen robotics Research center Yanshan Univers#y Qinhuangdao 066004 China

Since the traditional Griibler-Kutzbach criterion fails in many overconstrained mechanisms, developing a general mobility formula is a hot topic lasting for more than 150 years in mechanisms. GOGU systematically investigated various mobility methods, and pointed that the methods were not fit for two kinds of paradoxical overconstrained mechanisms. The mobility on the two kinds of mechanisms is regarded as ＂Gogu problem＂. The Modified Griibler-Kutzbach criterion has solved the mobility of the second kind of mechanisms in ＂Gogu problem＂, and has developed into a systematic mobility methodology. Myard 5R linkage is one of the single-loop mechanisms involved in ＂Gogu problem＂, its joint axes are distributed in space with special geometric conditions, which increases the difficulty of mobility analysis. The study is to calculate the global mobility of the Myard 5R linkage using the mobility methodology. Firstly, the mobility methodology based on screw theory is briefly introduced. Secondly, some homogeneous transforms are performed according to the D-H parameters and the invariance of the linkage plane symmetry is revealed, which provides an idea to judge a plane-symmetric loop. The special geometric features of the axes distribution are discussed as well. Finally, the global mobility of the Myard 5R linkage is determined by the Modified Grubler-Kutzbach criterion. The results show that the methodology can be applied to more paradoxical mechanisms.

关键词： overconstrained linkage screw theory mobility

Reinforcement learning based parameter optimization of active disturbance rejection control for autonomous underwater vehicle

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2022年第1期33卷 170-179页

作者： SONG Wanping CHEN Zengqiang SUN Mingwei SUN Qinglin College of artificial Intelligence Nankai UniversityTianjin 300350China Key Laboratory of Intelligent robotics of Tianjin Nankai UniversityTianjin 300350China

This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion *** the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC ***, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.

关键词： autonomous underwater vehicle(AUV) reinforcement learning(RL) Q-learning linear active disturbance rejection control(LADRC) motion decoupling parameter optimization

Distributed fuzzy fault-tolerant consensus of leader-follower multi-agent systems with mismatched uncertainties

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2021年第5期32卷 1031-1040页

作者： MALIKA Sader WANG Fuyong LIU Zhongxin CHEN Zengqiang College of artificial Intelligence Nankai UniversityTianjin 300350China Tianjin Key Laboratory of Intelligent robotics Nankai UniversityTianjin 300350China

In this paper,the distributed fuzzy fault-tolerant tracking consensus problem of leader-follower multi-agent systems(MASs)is *** objective system includes actuator faults,mismatched parameter uncertainties,nonlinear functions,and exogenous disturbances under switching communication *** solve this problem,a distributed fuzzy fault-tolerant controller is proposed for each follower by adaptive mechanisms to track the state of the ***,the fuzzy logic system is utilized to approximate the unknown nonlinear *** error estimator is introduced between the mismatched parameter matrix and the input ***,a selective adaptive law with relative state information is adopted and *** calculating the Lyapunov function’s derivative,the coupling terms related to consensus error and mismatched parameter uncertainties can be ***,a numerical simulation is given to validate the effectiveness of the proposed protocol.

关键词： distributed fuzzy fault-tolerant control(FTC) tracking consensus problem leader-follower multi-agent system mismatched parameter uncertainty

Temporality-enhanced knowledge memory network for factoid question answering

在线全文

学校读者我要写书评

暂无评论

Frontiers of Information Technology & Electronic Engineering 2018年第1期19卷 104-115页

作者： Xin-yu DUAN Si-liang TANG Sheng-yu ZHANG Yin ZHANG Zhou ZHAO Jian-ru XUE Yue-ting ZHUANG Fei WU College of Computer Science and Technology Zhejiang University School of Information Management Wuhan University Institute of artificial Intelligence and robotics Xi'an Jiaotong University

Question answering is an important problem that aims to deliver specific answers to questions posed by humans in natural *** to efficiently identify the exact answer with respect to a given question has become an active line of *** approaches in factoid question answering tasks typically focus on modeling the semantic relevance or syntactic relationship between a given question and its corresponding *** of these models suffer when a question contains very little content that is indicative of the *** this paper,we devise an architecture named the temporality-enhanced knowledge memory network(TE-KMN) and apply the model to a factoid question answering dataset from a trivia competition called quiz *** most of the existing approaches,our model encodes not only the content of questions and answers,but also the temporal cues in a sequence of ordered sentences which gradually remark the ***,our model collaboratively uses external knowledge for a better understanding of a given *** experimental results demonstrate that our method achieves better performance than several state-of-the-art methods.

关键词： Question answering Knowledge memory Temporality interaction

Optimization-inspired manual architecture design and neural architecture search

在线全文

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2023年第11期66卷 100-112页

作者： Yibo YANG Zhengyang SHEN Huan LI Zhouchen LIN JD Explore Academy School of Mathematical Sciences Peking University Institute of robotics and Automatic Information Systems College of Artificial Intelligence Nankai University Key Lab of General artificial Intelligence School of Intelligence Science and Technology Peking University Institute for artificial Intelligence Peking University Pazhou Lab

Neural architecture has been a research focus in recent years due to its importance in deciding the performance of deep networks. Representative ones include a residual network(Res Net) with skip connections and a dense network(Dense Net) with dense connections. However, a theoretical guidance for manual architecture design and neural architecture search(NAS) is still lacking. In this paper, we propose a manual architecture design framework, which is inspired by optimization algorithms. It is based on the conjecture that an optimization algorithm with a good convergence rate may imply a neural architecture with good performance. Concretely, we prove under certain conditions that forward propagation in a deep neural network is equivalent to the iterative optimization procedure of the gradient descent algorithm minimizing a cost function. Inspired by this correspondence, we derive neural architectures from fast optimization algorithms,including the heavy ball algorithm and Nesterov’s accelerated gradient descent algorithm. Surprisingly, we find that we can deem the Res Net and Dense Net as special cases of the optimization-inspired *** architectures offer not only theoretical guidance, but also good performances in image recognition on multiple datasets, including CIFAR-10, CIFAR-100, and Image Net. Moreover, we show that our method is also useful for NAS by offering a good initial search point or guiding the search space.

关键词： deep neural network manual architecture design neural architecture search image recognition optimization algorithms learning-based optimization

Surface defect detection competition with a bio-inspired vision sensor

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

National Science Review 2023年第6期10卷 31-34页

作者： Anjing Guo Jupo Ma Renwei Dian Fuyan Ma Jinjian Wu Shutao Li School of robotics Hunan University School of artificial Intelligence Xidian University Pazhou Laboratory (Huangpu) College of Electrical and Information Engineering Hunan University Key Laboratory of Visual Perception and artificial Intelligence of Hunan Province

INTRODUCTION Surface defects are inevitable during the product manufacturing process,such as impurities,scratches and dirt.D efects not only reduce the aesthetics and comfort of products,but may also degrade the functional *** are very concerned about inadequate defect detection because of potential economic and reputation ***,it is significant to study automatic defect detection *** machine vision-based defect detection mostly adopts a traditional CCD or CMOS vision sensor (VS) for ***,in real-world production lines,due to dynamic environments,traditional VS encounters difficulties in meeting the demands of defect detection,especially in modern high-precision product manufacturing.

关键词：

Efficient Nonnegative Tensor Decomposition Using Alternating Direction Proximal Method of Multipliers

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2024年第5期33卷 1308-1316页

作者： Deqing WANG Guoqiang HU State Key Laboratory of robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for robotics and Intelligent Manufacturing Chinese Academy of Sciences Key Laboratory of Marine robotics Liaoning Province College of artificial Intelligence Dalian Maritime University

Nonnegative CANDECOMP/PARAFAC（NCP） tensor decomposition is a powerful tool for multiway signal processing. The alternating direction method of multipliers（ADMM） optimization algorithm has become increasingly popular for solving tensor decomposition problems in the block coordinate descent framework. However,the ADMM-based NCP algorithm suffers from rank deficiency and slow convergence for some large-scale and highly sparse tensor data. The proximal algorithm is preferred to enhance optimization algorithms and improve convergence properties. In this study, we propose a novel NCP algorithm using the alternating direction proximal method of multipliers（ADPMM） that consists of the proximal algorithm. The proposed NCP algorithm can guarantee convergence and overcome the rank deficiency. Moreover, we implement the proposed NCP using an inexact scheme that alternatively optimizes the subproblems. Each subproblem is optimized by a finite number of inner iterations yielding fast computation speed. Our NCP algorithm is a hybrid of alternating optimization and ADPMM and is named *** experimental results on synthetic and real-world tensors demonstrate the effectiveness and efficiency of our proposed algorithm.

关键词： Tensors Neuroscience Signal processing algorithms Linearization techniques Signal processing Fluorescence Data processing

Part-based on-road vehicle detection using hidden random field

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2011年第12期54卷 2542-2549页

作者： ZHANG XueTao 1 , HE YongJian 1,2 & WANG Fei 1 1 Institute of artificial Intelligence and robotics, Xi’an Jiaotong University, Xi’an 710049, China 2 Xi’an Communication Institute, Xi’an 710049, China Institute of artificial Intelligence and robotics Xi’an Jiaotong University Xi’an China Xi’an Communication Institute Xi’an China

This paper addresses the problem of detecting on-road vehicles in still images captured by the on-board cameras. We model this as a labelling inference procedure and incorporate the part-based representation of the rear-ends of vehicle within a hidden random field based probabilistic model. Representing objects with parts inherently good for dealing with occlusions. In the proposed model, the part labels form a hidden layer in the graphical model. Our approaches can automatically find the latent parts without explicit indication during training. The experiment is performed on the database with real images with a promising result.

关键词： vehicle detection hidden random field part-based model