检索结果-内蒙古大学图书馆

arXiv 2021年

作者： Nguyen, Anh Tung Lee, Ji-Won Nguyen, Thanh Binh Hong, Sung Kyung Korea Republic of Human-Robot Interaction Research Center Korea Institute of Robotics and Technology Convergence Pohang37553 Korea Republic of Department of Control Engineering and Automation Thuyloi University 175 Tay Son Dong Da Hanoi Viet Nam

The utilisation of unmanned aerial vehicles has witnessed significant growth in real-world applications including surveillance tasks, military missions, and transportation deliveries. This letter investigates practical problems of formation control for multiple nano-quadrotor systems. To be more specific, the first aim of this work is to develop a theoretical framework for the time-varying formation flight of the multi-quadrotor system regarding anti-collisions. In order to achieve this goal, the finite cut-off potential function is devoted to avoiding collisions among vehicles in the group as well as between vehicles and an obstacle. The control algorithm navigates the group of nano-quadrotors to asymptotically reach an anticipated time-varying formation. The second aim is to implement the proposed algorithm on Crazyflies nano-quadrotors, one of the most ubiquitous indoor experimentation platforms. Several practical scenarios are conducted to tendentiously expose anti-collision abilities among group members as well as between vehicles and an obstacle. The experimental outcomes validate the effectiveness of the proposed method in the formation tracking and the collision avoidance of multiple nano-quadrotors. © 2021, CC BY.

关键词： Collision avoidance

来源：评论

学校读者我要写书评

暂无评论

Model-free design of stochastic lqr controller from reinforcement learning and primal-dual optimization perspective

arXiv

引用

arXiv 2021年

作者： Li, Man Qin, Jiahu Zheng, Wei Xing Wang, Yaonan Kang, Yu Department of Automation University of Science and Technology of China Hefei230027 China School of Computing Engineering and Mathematics Western Sydney University SydneyNSW2751 Australia College of Electrical and Information Engineering Hunan University Changsha410082 China National Engineering Laboratory for Robot Visual Perception and Control Technology Changsha410082 China

To further understand the underlying mechanism of various reinforcement learning (RL) algorithms and also to better use the optimization theory to make further progress in RL, many researchers begin to revisit the linear-quadratic regulator (LQR) problem, whose setting is simple and yet captures the characteristics of RL. Inspired by this, this work is concerned with the model-free design of stochastic LQR controller for linear systems subject to Gaussian noises, from the perspective of both RL and primal-dual optimization. From the RL perspective, we first develop a new model-free off-policy policy iteration (MF-OPPI) algorithm, in which the sampled data is repeatedly used for updating the policy to alleviate the data-hungry problem to some extent. We then provide a rigorous analysis for algorithm convergence by showing that the involved iterations are equivalent to the iterations in the classical policy iteration (PI) algorithm. From the perspective of optimization, we first reformulate the stochastic LQR problem at hand as a constrained non-convex optimization problem, which is shown to have strong duality. Then, to solve this non-convex optimization problem, we propose a model-based primal-dual (MBPD) algorithm based on the properties of the resulting Karush-Kuhn-Tucker (KKT) conditions. We also give a model-free implementation for the MB-PD algorithm by solving a transformed dual feasibility condition. More importantly, we show that the dual and primal update steps in the MB-PD algorithm can be interpreted as the policy evaluation and policy improvement steps in the PI algorithm, respectively. Finally, we provide one simulation example to show the performance of the proposed algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

An IGD+ Performance Indicator Based Particle Swarm Optimizer For Multi-objective Optimization

An IGD+ Performance Indicator Based Particle Swarm Optimizer...

引用

第33届中国控制与决策会议

作者： Fei Li Shijian Dong Yuanqu Liu Zhengkun Shang School of Electrical and Information Engineering Anhui Unviersity of Technology AnHui Province Key Laboratory of Special Heavy Load Robot Anhui Unviersity of Technology Ma'anshan University School of Information and Control Engineering China University of Mining and Technology Department of Automation North China Electric Power University

Particle swarm optimizer（PSO） is suitable for solving multi-objective optimization problems（MOPs）.However,there are two main issues for any multi-objective particle swarm optimizers（MOPSOs）.The first issue is how to balance the convergence and *** second issue is how to enhance the exploitation and exploration during the evolutionary *** order to address these issues,an modified inverted generational distance（IGD） performance indicator based PSO（IGD-MOPSO） is *** external archive updating strategies based on the IGD indicator and the objective space decomposition method are proposed to select the evenly distributed non-dominated *** leader updated strategy of each particle is based on the IGD indicator value which is associated to the corresponding reference *** genetic operator is embedded into the evolutionary procedure to reset the position in order to help the particle jump out of the local *** have conducted the simulation on some related benchmark test *** experimental results have indicated that the proposed algorithm is competitive with some related algorithms.

关键词： IGD+ indicator Particle swarm optimization The external archive updated strategy Objective space decomposition Multi-objective optimization problems

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence based framework for robotic search and rescue operations conducted jointly by international teams 14th

Artificial intelligence based framework for robotic search a...

引用

14th International Conference on Electromechanics and robotics - Zavalishin's Readings, ER(ZR) 2019

作者： Magid, Evgeni Pashkin, Artyom Simakov, Nikita Abbyasov, Bulat Suthakorn, Jackrit Svinin, Mikhail Matsuno, Fumitoshi Kazan Federal University 35 Kremlyovskaya Street Kazan420008 Russia Biomedical Engineering Department Mahidol University 4 999 Phuttamonthon Salaya73170 Thailand Robot Dynamics and Control Laboratory College of Information Science and Engineering Ritsumeikan University Noji Higashi 1-1-1 Kusatsu525-8577 Japan Mechanical Engineering and Science Department Kyoto University 3 Kyoudaikatsura Nishigyo-Ku Kyoto615-8540 Japan

ISBN: (纸本)9789811392665

Many countries suffer from various natural disasters, including heavy rains, that are associated with further flood and landslide disasters. Based on our experiences of different disasters response, we develop a joint international operation framework for a disaster site management with distributed heterogeneous robotic teams that consist of unmanned aerial, ground, surface, and underwater vehicles. The artificial intelligence-based information collection system, which is targeting to become a worldwide standard, contains interaction protocols, thematic mapping approaches, and map fusion processes. The project provides a new working framework and control strategies for heterogeneous robotic teams’ cooperative behavior in sensing, monitoring, and mapping of flood and landslide disaster areas. In this paper, we present an overview of the system and a first stage toward robot interaction protocols development and the system modeling within robot operating system’s Gazebo environment. © Springer Nature Singapore Pte Ltd 2020.

关键词： robotics

来源：评论

学校读者我要写书评

暂无评论

Mura Defect Detection on Compact Camera Module (CCM) Using Metric Learning

Mura Defect Detection on Compact Camera Module (CCM) Using M...

引用

IEEE International Conference on Automation Science and engineering (CASE)

作者： Y. G. Kim T. H. Park Department of Control and Robot Engineering Chungbuk National University Cheongju-si Republic of Korea School of Electronics Engineering Chungbuk National University Cheongju-si Republic of Korea

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

The Compact Camera Module (CCM) is a device used for various compact electronic devices such as notebooks, smartphones, etc. Various defects occur in the manufacturing process, such as scratches, stamps, and mura. Most notably, mura defect detection is the most challenging issue because of how normal it appears. With this, various methods based on deep learning have been developed to detect mura defects. However, previous research assumes that there is a substantial amount of training data. Therefore, classification accuracy decreases in an environment wherein it is difficult to obtain a sample of an actual defect. This study proposes a metric learning-based mura defect detection method with higher classification accuracy than the previous semantic segmentation method in an environment with little training data. In the training phase, we obtained the center of the normal metric vector of the input image through the metric embedding model and metric loss, while in the test stage, we detected the mura defect based on the center of the normal metric vector. The experimental results show that the proposed method has higher detection accuracy than the previous method in an environment with few training data.

关键词： Measurement Feature extraction Semantics Image segmentation Training Training data Load modeling

来源：评论

学校读者我要写书评

暂无评论

SHUYU robot:An Automatic Rapid Temperature Screening System

引用

Chinese Journal of Mechanical engineering 2020年第2期33卷 1-4页

作者： Zhao Gong Songwen Jiang Qizhi Meng Yanlei Ye Peng Li Fugui Xie Huichan Zhao Chunzhe Lv Xiaojie Wang Xinjun Liu The State Key Laboratory of Tribology&Tsinghua University(DME)‑Siemens Joint Research Center for Advanced Robotics Department of Mechanical Engineering(DME)Tsinghua UniversityBeijing 100084China Beijing Key Lab of Precision/Ultra‑precision Manufacturing Equipments and Control Tsinghua UniversityBeijing 100084China Yantai Tsingke+Robot Joint Research Institute Co. Ltd.Yantai 264000ShandongChina The First Affiliated Hospital of Tsinghua University Beijing 100016China

The health of people around the world and the global economy are under substantial threat from the outbreak of pandemics[1].controlling pandemics is extremely challenging,with preventing the spread of pathogens the most important and critical *** all preventative actions,body temperature screening is undoubtedly highly necessary and effective[2].

关键词： robot doubt critical

来源：评论

学校读者我要写书评

暂无评论

Visual Object Detection Based LiDAR Point Cloud Classification

Visual Object Detection Based LiDAR Point Cloud Classificati...

引用

International Conference on Big Data and Smart Computing (BIGCOMP)

作者： Sualeh Muhammad Gon-Woo Kim Intelligent Robotics Laboratory Control and Robot Engineering Department Chungbuk National University Cheongju Republic of Korea Chungbuk National University Cheongju South Korea

ISBN: (数字)9781728160344

ISBN: (纸本)9781728160351

The environmental perception plays a pivotal role in autonomous driving tasks and demands robustness in cluttered dynamic environments such as complex urban scenarios. LiDAR being one of the popular perceptual sensor, suffers with large number of inaccurate object detections. This work is an extension of an ongoing research on multiple object detection and tracking. Where, Neural Network based approach is considered for visual detection to aid the LiDAR point cloud processing, and to address the inherent shortcoming of the sensor. It is inferred that the proposed framework would perform in real-time on an embedded platform. In addition, the separate processing of visual and LiDAR sensor data will enable switching to a light weight LiDAR only setup in runtime when required.

关键词： Three-dimensional displays Laser radar Object detection Visualization robot sensing systems Task analysis Cameras

来源：评论

学校读者我要写书评

暂无评论

Adaptive finite-time synchronized control of multi-robotic fiber placement system with model uncertainties and disturbances

引用

ISA transactions 2025年

作者： Ronghua Zhang Yaonan Wang Wenfang Xie Pengcheng Li Haoran Tan Yiming Jiang College of Electrical and Information Engineering Hunan University Changsha 410082 Hunan China National Engineering Laboratory of Robot Visual Perception and Control Technology Hunan University Changsha 410082 Hunan China. Department of Mechanical Industrial and Aerospace Concordia University Montreal H3G2W1 Quebec Canada. College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics Nanjing 210016 Jiangsu China. National Engineering Laboratory of Robot Visual Perception and Control Technology Hunan University Changsha 410082 Hunan China. Electronic address: tanhaoran@***. School of Robotics Hunan University Changsha 410082 Hunan China

The use of multiple robots to manufacture composite components represents a critical development direction for fiber placement systems (FPSs). In multi-robotic fiber placement systems (MRFPSs) with heterogeneous mechanical structures, robots collaborate to perform fiber placement tasks. Consequently, robot synchronization emerges as a primary factor in determining the performance of the fiber placement process. However, the difficulty in establishing accurate system models and the presence of disturbances are two significant challenges to achieving precise robot synchronization. Additionally, the system is expected to exhibit desirable dynamic characteristics, such as finite-time error convergence. To address these issues and requirements, we propose a novel adaptive finite-time synchronization control (AFSC) algorithm for the system. Specifically, a finite-time sliding mode observer is developed to handle kinematic uncertainty. A novel fast non-singular terminal sliding mode (FNTSM) manifold is constructed in the AFSC algorithm. Moreover, the control algorithm integrates an adaptive law to handle dynamic uncertainty and an adaptive term to counteract disturbances. Performance analysis demonstrates that the AFSC ensures that the coupled, synchronization, and tracking errors converge to zero within finite time. Furthermore, simulations and experiments are conducted to validate the effectiveness of the AFSC algorithm.

关键词： Disturbances Fiber placement Finite-time control Model uncertainties Multi-robots Synchronization control

来源：评论

学校读者我要写书评

暂无评论

Towards to robust and generalized medical image segmentation framework

arXiv

引用

arXiv 2021年

作者： Chen, Yurong Zhang, Hui Wang, Yaonan Liu, Lizhu Wu, Q.M. Jonathan Yang, Yimin National Engineering Laboratory of Robot Visual Perception and Control Technology School of Robotics Hunan University Hunan Changsha410082 China Department of Electrical and Computer Engineering University of Windsor WindsorONN9B3P4 Canada Department of Computer Science Lakehead University Vector Institute TorontoM5G 1M1 Canada

—To mitigate the radiologist’s workload, computer-aided diagnosis with the capability to review and analyze medical images is gradually deployed. Deep learning-based region of interest segmentation is among the most exciting use cases. However, this paradigm is restricted in real-world clinical applications due to the poor robustness and generalization. The issue is more sinister with a lack of training data. In this paper, we address the challenge from the representation learning point of view. We investigate that the collapsed representations, as one of the main reasons which caused poor robustness and generalization, could be avoided through transfer learning. Therefore, we propose a novel two-stage framework for robust generalized segmentation. In particular, an unsupervised Tile-wise AutoEncoder (T-AE) pretraining architecture is coined to learn meaningful representation. Furthermore, this learned prior knowledge is transferred to the segmentation benchmark. Coupled with an image reconstruction network, the representation keeps to be decoded, encouraging the model to capture more semantic features. Experiments of lung segmentation on multi chest X-ray datasets are conducted. Empirically, the comprehensive results demonstrate the superior generalization capability of the proposed framework on unseen domains in terms of high performance and robustness to corruption, especially under the scenario of the limited training data. © 2021, CC BY.

关键词： Computer aided diagnosis

来源：评论

学校读者我要写书评

暂无评论

Automatic basketball detection in sport video based on R-FCN and soft-NMS 2019

Automatic basketball detection in sport video based on R-FCN...

引用

4th International Conference on Automation, control and robotics engineering, CACRE 2019

作者： Liang, Qiaokang Mei, Li Wu, Wanneng Sun, Wei Wang, Yaonan Zhang, Dan Key Laboratory of Intelligent Robot Technology in Electronic Manufacturing National Engineering Laboratory for Robot Vision Perception and Control Hunan University Changsha410082 China Department of Mechanical Engineering York University TorontoM3J 1P3 Canada

ISBN: (纸本)9781450371865

In basketball videos, the ball is always so small in the camera that its appearance feature is hard to be extracted. In this paper, we introduce a deep-learning technology to detect the basketball. Specifically, we train our basketball detection model based on the Region-based Fully Convolutional Networks (R-FCN) which uses the fully convolutional Residual Network (ResNet) as the backbone network. What’s more, we apply some new techniques including Online Hard Example Mining (OHEM), Soft-NMS and multi-scale training strategy to achieve higher detection accuracy. In detail, the OHEM method can reduce the cost of fine-tuning during training by calculating the loss of the RoIs. Soft-NMS can reduce the false positive rate by decreasing the object detection score between the overlap object. And the multi-scale training can improve the detection performance by receiving the good feature from the object with different scale. Finally, we achieve a mean average precision (mAP) value of 89.7% on a public basketball dataset. It proves that applying the deep-learning approach to basketball detection is effective. © 2019 Copyright is held by the owner/author(s).

关键词： Object recognition

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：