检索结果-内蒙古大学图书馆

Neighborhood Interval Observer Based Coordination control for Multi-agent Systems with Disturbances ⁎

学校读者我要写书评

暂无评论

IFAC-PapersOnLine 2020年第2期53卷 10994-10999页

作者： Xiaoling Wang Guo-Ping Jiang Wen Yang Housheng Su Xiaofan Wang College of Automation Nanjing University of Posts and Telecommunications Nanjing 210023 China and also with Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing 210023 China Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai 200237 China School of Artifcial Intelligence and Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China Department of Automation Shanghai University Shanghai 200072 China

This paper focuses on multi-agent systems with uncertain disturbances, in which only the bounding functions on the disturbances and the bounds on the initial state of each agent are known. By designing a neighborhood interval observer for this kind of multi-agent system, the estimation of the sum of the relative state of each agent associated with itself and its neighbors is frstly realized. Then, on the basis of these estimated information, local control algorithm is designed to drive the system to achieve bounded consensus.

关键词： Multi-agent system disturbance neighborhood interval observer bounded consensus

Input-Output Optics as a Causal Time Series Mapping: A Generative Machine Learning Solution

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Sen, Abhijit Parida, Bikram Keshari Jacobs, Kurt Bondar, Denys I. Department of Physics and Engineering Physics Tulane University New OrleansLA70118 United States Artificial Intelligence & Image Processing Lab. Sun Moon University Asan-Si Korea Republic of United States DEVCOM Army Research Laboratory AdelphiMD20783 United States Department of Physics University of Massachusetts at Boston BostonMA02125 United States

The response of many-body quantum systems to an optical pulse can be extremely challenging to model. Here we explore the use of neural networks, both traditional and generative, to learn and thus simulate the response of such a system from data. The quantum system can be viewed as performing a complex mapping from an input time-series (the optical pulse) to an output time-series (the systems response) which is often also an optical pulse. Using both the transverse and non-integrable Ising models as examples, we show that not only can temporal convolutional networks capture the input/output mapping generated by the system but can also be used to characterize the complexity of the mapping. This measure of complexity is provided by the size of the smallest latent space that is able to accurately model the mapping. We further find that a generative model, in particular a variational auto-encoder, significantly outperforms traditional auto-encoders at learning the complex response of many-body quantum systems. For the example that generated the most complex mapping, the variational auto-encoder produces outputs that have less than 10% error for more than 90% of inputs across our test data. Copyright © 2024, The Authors. All rights reserved.

关键词： Time series

Switched High-Gain Based Interval Observer Design for Harmonic Oscillator System

学校读者我要写书评

暂无评论

Switched High-Gain Based Interval Observer Design for Harmon...

Chinese control Conference (CCC)

作者： Tianhang Ming Xiaoling Wang Bo Liu Housheng Su College of Automation & AI Nanjing University of Posts and Telecommunications Nanjing P. R. China Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing China College of Information Engineering Minzu University of China Beijing P. R. China Key Laboratory of Image Processing and Intelligence Control of Ministry of Education Huazhong University of Science and Technology Wuhan P. R. China

In this paper, we revisit the interval observer design problem of harmonic oscillator system with unknown but bounded external disturbance and measurement noise. With the bounding information of the external disturbance and measurement noise, a high-gain interval observer is firstly defined and constructed for the harmonic oscillator system to realize the interval estimation on the state and the robust control of the system. Then, a switched high-gain interval observer is proposed to reduce the influence of the measurement noise for a tighter interval width on the state estimation. Finally, some numerical simulations are given to verify the theoretical results.

关键词：

Utility-Oriented Underwater image Quality Assessment Based on Transfer Learning

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Chen, Weiling Lin, Rongfu Liao, Honggang Zhao, Tiesong Gu, Ke Le Callet, Patrick Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information Fuzhou University Fuzhou350108 China Peng Cheng Laboratory Shenzhen518000 China The Faculty of Information Technology Beijing University of Technology Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China Équipe Image Perception et Interaction Laboratoire des Sciences du Numérique de Nantes Université de Nantes France

The widespread image applications have greatly promoted the vision-based tasks, in which the image Quality Assessment (IQA) technique has become an increasingly significant issue. For user enjoyment in multimedia systems, the IQA exploits image fidelity and aesthetics to characterize user experience;while for other tasks such as popular object recognition, there exists a low correlation between utilities and perceptions. In such cases, the fidelity-based and aesthetics-based IQA methods cannot be directly applied. To address this issue, this paper proposes a utility-oriented IQA in object recognition. In particular, we initialize our research in the scenario of underwater fish detection, which is a critical task that has not yet been perfectly addressed. Based on this task, we build an Underwater image Utility Database (UIUD) and a learning-based Underwater image Utility Measure (UIUM). Inspired by the top-down design of fidelity-based IQA, we exploit the deep models of object recognition and transfer their features to our UIUM. Experiments validate that the proposed transfer-learning-based UIUM achieves promising performance in the recognition task. We envision our research provides insights to bridge the researches of IQA and computer vision. Copyright © 2022, The Authors. All rights reserved.

关键词： Multimedia systems

Coordinated Guiding Vector Field Design for Ordering-Flexible Multi-Robot Surface Navigation

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Hu, Bin-Bin Zhang, Hai-Tao Yao, Weijia Sun, Zhiyong Cao, Ming The School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China The School of Robotics Hunan University Hunan410082 China The Institute of Engineering and Technology University of Groningen Groningen9747 AG Netherlands Department of Electrical Engineering Eindhoven University of Technology Netherlands

We design a distributed coordinated guiding vector field (CGVF) for a group of robots to achieve ordering-flexible motion coordination while maneuvering on a desired two-dimensional (2D) surface. The CGVF is characterized by three terms, i.e., a convergence term to drive the robots to converge to the desired surface, a propagation term to provide a traversing direction for maneuvering on the desired surface, and a coordinated term to achieve the surface motion coordination with an arbitrary ordering of the robotic group. By setting the surface parameters as additional virtual coordinates, the proposed approach eliminates potential singularity of the CGVF and enables both the global convergence to the desired surface and the maneuvering on the surface from all possible initial conditions. The ordering-flexible surface motion coordination is realized by each robot to share with its neighbors only two virtual coordinates, i.e. that of a given target and that of its own, which reduces the communication and computation cost in multi-robot surface navigation. Finally, the effectiveness of the CGVF is substantiated by extensive numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Navigation

Zero-shot Text-driven Physically Interpretable Face Editing

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Meng, Yapeng Yang, Songru Hu, Xu Zhao, Rui Li, Lincheng Shi, Zhenwei Zou, Zhengxia Image Processing Center School of Astronautics Beihang University Beijing100191 China Beijing Key Laboratory of Digital Media Beihang University Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China Shanghai Artificial Intelligence Laboratory China The Netease Fuxi AI Lab Hangzhou China The Department of Guidance Navigation and Control School of Astronautics Beihang University Beijing100191 China

This paper proposes a novel and physically interpretable method for face editing based on arbitrary text prompts. Different from previous GAN-inversion-based face editing methods that manipulate the latent space of GANs, or diffusion-based methods that model image manipulation as a reverse diffusion process, we regard the face editing process as imposing vector flow fields on face images, representing the offset of spatial coordinates and color for each image pixel. Under the above-proposed paradigm, we represent the vector flow field in two ways: 1) explicitly represent the flow vectors with rasterized tensors, and 2) implicitly parameterize the flow vectors as continuous, smooth, and resolution-agnostic neural fields, by leveraging the recent advances of implicit neural representations. The flow vectors are iteratively optimized under the guidance of the pre-trained Contrastive Language-image Pretraining (CLIP) model by maximizing the correlation between the edited image and the text prompt. We also propose a learning-based one-shot face editing framework, which is fast and adaptable to any text prompt input. Our method can also be flexibly extended to real-time video face editing. Compared with state-of-the-art text-driven face editing methods, our method can generate physically interpretable face editing results with high identity consistency and image quality. Our code will be made publicly availab.e. © 2023, CC BY-NC-SA.

关键词： Iterative methods

Physics Informed Kolmogorov-Arnold Neural Networks for Dynamical Analysis via Efficent-KAN and WAV-KAN

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Patra, Subhajit Panda, Sonali Parida, Bikram Keshari Arya, Mahima Jacobs, Kurt Bondar, Denys I. Sen, Abhijit Department of Electrical Engineering Indian Institute of Technology Delhi India Department of Physics Indian Institute of Technology Dhanbad India Artificial Intelligence and Image Processing Lab. Sun Moon University Korea Republic of School of Artificial Intelligence Amrita Vishwa Vidyapeetham Coimbatore641112 India United States DEVCOM Army Research Laboratory AdelphiMD20783 United States Department of Physics University of Massachusetts at Boston BostonMA02125 United States Department of Physics and Engineering Physics Tulane University New OrleansLA70118 United States

Physics-informed neural networks have proven to be a powerful tool for solving differential equations, leveraging the principles of physics to inform the learning process. However, traditional deep neural networks often face challenges in achieving high accuracy without incurring significant computational costs. In this work, we implement the Physics-Informed Kolmogorov-Arnold Neural Networks (PIKAN) through efficient-KAN and WAV-KAN, which utilize the Kolmogorov-Arnold representation theorem. PIKAN demonstrates superior performance compared to conventional deep neural networks, achieving the same level of accuracy with fewer layers and reduced computational overhead. We explore both B-spline and wavelet-based implementations of PIKAN and benchmark their performance across various ordinary and partial differential equations using unsupervised (data-free) and supervised (data-driven) techniques. For certain differential equations, the data-free approach suffices to find accurate solutions, while in more complex scenarios, the data-driven method enhances the PIKAN’s ability to converge to the correct solution. We validate our results against numerical solutions and achieve 99% accuracy in most scenarios. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep neural networks

Scene matching based on non-linear pre-processing on reference image and sensed image

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2005年第2期000卷

作者： ZHONG Sheng Zhang Tianxu Sang Nong State Key Lab for Image Processing & Intelligent Control， Institute for Pattern Recognition and Artificial Intelligence，Huazhong University of Science and Technology， Wuhan 430074， P. R. China

To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability... 详细信息

关键词： intensity-based correlation heterogeneous image scene matching

Manipulab.lity and Robustness Optimization of the Cable-Driven Redundant Soft Manipulator

学校读者我要写书评

暂无评论

Manipulability and Robustness Optimization of the Cable-Driv...

IEEE International Conference on Robotics and Biomimetics

作者： Yi Shen Yang Hong Wei Zhou Ruochen Tai Ye Yuan Han Ding School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan People’s Republic of China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan People’s Republic of China State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan People’s Republic of China

ISBN: (纸本)9781665405362

Redundancy makes soft manipulators manage to complete a variety of tasks in complex environments. However, a pseudo-inverse kinematics controller for redundant soft manipulators simply maximizes the manipulab.lity while ignoring some material constraints, e.g., actuation saturation and control noise. As manipulab.lity is the indicator for the dexterity of motion in all directions of the redundant soft manipulators, this work proposes an optimization based controller, where the manipulab.lity and robustness are optimized for a cable-driven redundant soft manipulator to adapt actuation saturation and control noise. Experiments are conducted to demonstrate the effectiveness of the proposed controller.

关键词： Conferences Biomimetics Redundancy Kinematics Manipulators Robustness Trajectory