检索结果-内蒙古大学图书馆

arXiv 2022年

作者： Jiang, Chaokang Wang, Guangming Miao, Yanzi Wang, Hesheng Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

3D scene flow characterizes how the points at the current time flow to the next time in the 3D Euclidean space, which possesses the capacity to infer autonomously the non-rigid motion of all objects in the scene. The previous methods for estimating scene flow from images have limitations, which split the holistic nature of 3D scene flow by estimating optical flow and disparity separately. Learning 3D scene flow from point clouds also faces the difficulties of the gap between synthesized and real data and the sparsity of LiDAR point clouds. In this paper, the generated dense depth map is utilized to obtain explicit 3D coordinates, which achieves direct learning of 3D scene flow from 2D images. The stability of the predicted scene flow is improved by introducing the dense nature of 2D pixels into the 3D space. Outliers in the generated 3D point cloud are removed by statistical methods to weaken the impact of noisy points on the 3D scene flow estimation task. Disparity consistency loss is proposed to achieve more effective unsupervised learning of 3D scene flow. The proposed method of self-supervised learning of 3D scene flow on real-world images is compared with a variety of methods for learning on the synthesized dataset and learning on LiDAR point clouds. The comparisons of multiple scene flow metrics are shown to demonstrate the effectiveness and superiority of introducing pseudo-LiDAR point cloud to scene flow estimation. © 2022, CC BY.

关键词： Three dimensional computer graphics

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Learning of 3D Scene Flow with 3D Odometry Assistance

arXiv

引用

arXiv 2022年

作者： Wang, Guangming Feng, Zhiheng Jiang, Chaokang Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China

Scene flow represents the 3D motion of each point in the scene, which explicitly describes the distance and the direction of each point’s movement. Scene flow estimation is used in various applications such as autonomous driving fields, activity recognition, and virtual reality fields. As it is challenging to annotate scene flow with ground truth for real-world data, this leaves no real-world dataset available to provide a large amount of data with ground truth for scene flow estimation. Therefore, many works use synthesized data to pre-train their network and real-world LiDAR data to finetune. Unlike the previous unsupervised learning of scene flow in point clouds, we propose to use odometry information to assist the unsupervised learning of scene flow and use real-world LiDAR data to train our network. Supervised odometry provides more accurate shared cost volume for scene flow. In addition, the proposed network has mask-weighted warp layers to get a more accurate predicted point cloud. The warp operation means applying an estimated pose transformation or scene flow to a source point cloud to obtain a predicted point cloud and is the key to refining scene flow from coarse to fine. When performing warp operations, the points in different states use different weights for the pose transformation and scene flow transformation. We classify the states of points as static, dynamic, and occluded, where the static masks are used to divide static and dynamic points, and the occlusion masks are used to divide occluded points. The mask-weighted warp layer indicates that static masks and occlusion masks are used as weights when performing warp operations. Our designs are proved to be effective in ablation experiments. The experiment results show the promising prospect of an odometry-assisted unsupervised learning method for 3D scene flow in real-world data. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

TTC4MCP: Monocular Collision Prediction Based on Self-Supervised TTC Estimation

TTC4MCP: Monocular Collision Prediction Based on Self-Superv...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Changlin Li Yeqiang Qian Cong Sun Weihao Yan Chunxiang Wang Ming Yang Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Global Institute of Future Technology Shanghai Jiao Tong University Shanghai China University of Michigan-Shanghai Jiao Tong University Joint Institute ShanghaiJiao Tong University Shanghai China

Vision-based collision prediction for autonomous driving is a challenging task due to the dynamic movement of vehicles and diverse types of obstacles. Most existing methods rely on object detection algorithms, which only predict predefined collision targets, such as vehicles and pedestrians, and cannot anticipate emergencies caused by unknown obstacles. To address this limitation, we propose a novel approach using pixel-wise time-to-collision (TTC) estimation for monocular collision prediction (TTC4MCP). Our approach predicts TTC and optical flow from monocular images and identifies potential collision areas using feature clustering and motion analysis. To overcome the challenge of training TTC estimation models without ground truth data in new scenes, we propose a self-supervised TTC training method, enabling collision prediction in a wider range of scenarios. TTC4MCP is evaluated on multiple road conditions and demonstrates promising results in terms of accuracy and robustness.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Tracking Performance of Networked Systems with Limited Bandwidth and Colored Noise

Tracking Performance of Networked Systems with Limited Bandw...

引用

Chinese automation Congress (CAC)

作者： Bin Zhang Xiaowei Jiang Li Sun Xianhe Zhang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China School of Statistics and Mathematics Zhongnan University of Economics and Law Wuhan China School of Electrical Engineering and Automation Hubei Normal University Huangshi China

This study investigated the optimal tracking performance (OTP) of multi-input multi-output (MIMO), discrete- time networked control systems (NCSs). The limits of tracking performance (TP) under the influences of bandwidth, encoding- decoding, and additive coloured Gaussian noise (ACGN) are derived using the techniques of coprime decomposition and all-pass decomposition. The results reveal the negative impact of non-minimum phase (NMP) zeros and unstable poles of the plant as well as network communication constraints on the TP of NCSs. Finally, a numerical simulation is discussed and verifies our conclusions.

关键词： Networked control systems Gaussian noise Bandwidth Numerical simulation Downlink Decoding Colored noise

来源：评论

学校读者我要写书评

暂无评论

Optimizing Neural Network Image Classification with Fractional Order Gradient Methods

SSRN

引用

SSRN 2023年

作者： Zhao, Haiming Chen, Jiejie Jiang, Ping Zeng, Zhigang Fan, Rui Yang, Honggang School of Computer and Information Engineering Hubei Normal University Huangshi435000 China School of Automation Wuhan University of Technology Wuhan430000 China School of Computer Hubei PolyTechnic University Huangshi435000 China Faculty of Artificial Intelligence Education Central China Normal University Wuhan430000 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430000 China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education of China Wuhan430000 China

As deep learning technology increasingly permeates various fields, the significance of optimization algorithms in neural network training has become more prominent. Typically, the training of deep learning networks relies on gradient descent optimizers based on calculus computations. Traditional integer-order calculus optimizers often fall short when dealing with complex and subtle data. To overcome these limitations, we innovatively utilized the Grünwald-Letnikov and Caputo definitions of fractional calculus to develop two new optimization algorithms: Fractional Order Adagrad (FAdagrad) and Fractional Order Adam (FAdam). These algorithms have been proven to converge to extremal points.A key advantage of our methods is their capability in handling complex, high-dimensional tasks, such as artistic painting image classification, where they exhibit exceptional performance in recognizing and processing subtle differences. The robustness and adaptability of these algorithms were further validated through experiments on the CIFAR-100 dataset. The results demonstrate the efficacy of fractional order optimizers in enhancing training efficiency and accuracy. © 2023, The Authors. All rights reserved.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

A Cutting Strategy for Customized Production of Wooden Components Based on industrial Internet

A Cutting Strategy for Customized Production of Wooden Compo...

引用

Chinese automation Congress (CAC)

作者： Ye Lin Dan Chen Zhezhuang Xu Shijia Liang Yang Qiu Xinxiang Liu Key Laboratory of Industrial Automation Control Technology and Information Processing College of Electrical Engineering and Automation Fuzhou University Fuzhou China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

In the wooden furniture industry, the increasing demand of mass customized production generates the diversity of customized wooden components that brings a challenge to the design of the cutting strategy. In this paper, we propose a framework for the cross cutting of wooden boards based on industrial internet. The list of customized wooden components are updated on demand by the production management server, and then transmitted to the industrial computer through industrial internet. Based on the information of the components and the scanned wooden board, the computer executes the cutting strategy to obtain the cutting list in real time. Then it is sent to the saw for the cross cutting. The proposed cutting strategy contains three algorithms: optimization of fixed-length components with uniform quality, matching component to wooden board in intervals, and processing continuous-length components. The experimental results verify the effectiveness of the proposed cutting strategy.

关键词： Real-time systems Servers Optimization Dynamic programming Production management Heuristic algorithms Sensors

来源：评论

学校读者我要写书评

暂无评论

Wood Color Classification Based on Color Spatial Features and K-means Algorithm

Wood Color Classification Based on Color Spatial Features an...

引用

Annual Conference of industrial Electronics Society

作者： Ye Lin Dan Chen Shijia Liang Yang Qiu Zhezhuang Xu Jiahao Zhang Xinxiang Liu School of Electrical Engineering and Automation Fuzhou University China Key Laboratory of Industrial Automation Control Technology and Information Processing China

ISBN: (数字)9781728154145

ISBN: (纸本)9781728154152

Wood color classification is used to classify the set of wooden boards with similar colors. It is helpful to improve the appearance of the wooden furniture which is spliced by multiple wooden boards. Due to the similarity of colors among wooden boards, the manual color classification is inaccurate and unstable, thus the supervised learning algorithms can hardly be used in this scenario. Moreover, the wooden board is long and its image has high resolution that may lead to the growth of computation complexity. To overcome these challenges, in this paper, we propose a new mechanism for wood color classification with the support of cloud and edge computing. The wood image is preprocessed to subtract irrelevant colors. Then the feature vector is extracted based on 3-D color histogram to reduce the computation complexity. In the offline clustering, the feature vector sets are partitioned into different clusters through K-means algorithm in the cloud server. The clustering result can be used in the online classification to classify the new wood image by the edge server. The experimental results verify the effectiveness of the proposed mechanism.

关键词： Image color analysis Feature extraction Servers Clustering algorithms Classification algorithms Surface treatment Partitioning algorithms

来源：评论

学校读者我要写书评

暂无评论

Stochastic Gradient-based Fast Distributed Multi-Energy Management for an industrial Park with Temporally-Coupled Constraints

arXiv

引用

arXiv 2022年

作者： Zhu, Dafeng Yang, Bo Ma, Chengbin Wang, Zhaojian Zhu, Shanying Ma, Kai Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China

Contemporary industrial parks are challenged by the growing concerns about high cost and low efficiency of energy supply. Moreover, in the case of uncertain supply/demand, how to mobilize delay-tolerant elastic loads and compensate real-time inelastic loads to match multi-energy generation/storage and minimize energy cost is a key issue. Since energy management is hardly to be implemented offline without knowing statistical information of random variables, this paper presents a systematic online energy cost minimization framework to fulfill the complementary utilization of multi-energy with time-varying generation, demand and price. Specifically to achieve charging/discharging constraints due to storage and short-term energy balancing, a fast distributed algorithm based on stochastic gradient with two-timescale implementation is proposed to ensure online implementation. To reduce the peak loads, an incentive mechanism is implemented by estimating users' willingness to shift. Analytical results on parameter setting are also given to guarantee feasibility and optimality of the proposed design. Numerical results show that when the bid-ask spread of electricity is small enough, the proposed algorithm can achieve the close-to-optimal cost asymptotically. © 2022, CC BY-NC-ND.

关键词： Energy management

来源：评论

学校读者我要写书评

暂无评论

A Pricing Rule for Third-Party Platoon Coordination Service Provider

A Pricing Rule for Third-Party Platoon Coordination Service ...

引用

Asian control Conference

作者： Ting Bai Alexander Johansson Shaoyuan Li Karl Henrik Johansson Jonas Må rtensson Integrated Transport Research Lab Digital Futures and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China

We model a platooning system including trucks and a third-party service provider that performs platoon coordination, distributes the platooning profit within platoons, and charges the trucks in exchange for its services. This paper studies one class of pricing rules, where the third-party service provider keeps part of the platooning profit each time a platoon is formed. Furthermore, we propose a platoon coordination solution based on distributed model predictive control in which the pricing rule is integrated. To evaluate the effect of the pricing on the platooning system, we perform a simulation over the Swedish road network. The simulation shows that the platooning rate and profit highly depend on the pricing. This suggests that pricing needs to be set carefully to obtain a satisfactory platooning system in the future.

关键词： Roads Pricing Predictive control

来源：评论

学校读者我要写书评

暂无评论

Fuzzy DNA Strand Displacement: A Strategy to Decrease the Complexity of DNA Network Design

引用

Angewandte Chemie 2020年第35期132卷 15089-15095页

作者： Wang Z. Hu Y. Pan L. Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China College of Information Science and Technology Shijiazhuang Tiedao University Shijiazhuang 050043 China

Toehold-mediated DNA strand displacement endows DNA nanostructures with dynamic response capability. However, the complexity of sequence design dramatically increases as the size of the DNA network increases. We attribute this problem to the mechanism of toehold-mediated strand displacement, termed exact strand displacement (ESD), in which one input strand corresponds to one specific substrate. In this work, we propose an alternative to toehold-mediated DNA strand displacement, termed fuzzy strand displacement (FSD), in which one-to-many and many-to-one relationships are established between the input strand and the substrate, to reduce the complexity. We have constructed four modules, termed converter, reporter, fuzzy detector, and fuzzy trigger, and demonstrated that a sequence pattern recognition network composed of these modules requires less complex sequence design than an equivalent network based on toehold-mediated DNA strand displacement. © 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

关键词： DNA recognition DNA structures enzymes molecular devices self-assembly

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：