检索结果-内蒙古大学图书馆

3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Wang, Guangming Zhong, Jiquan Zhao, Shijie Wu, Wenhua Liu, Zhe Wang, Hesheng Department of Automation Institute of Medical Robotics 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 Department of Engineering Mechanics Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Technology University of Cambridge CambridgeCB2 1TN United Kingdom

Depth and ego-motion estimations are essential for the localization and navigation of autonomous robots and autonomous driving. Recent studies make it possible to learn the per-pixel depth and ego-motion from the unlabeled monocular video. A novel unsupervised training framework is proposed with 3D hierarchical refinement and augmentation using explicit 3D geometry. In this framework, the depth and pose estimations are hierarchically and mutually coupled to refine the estimated pose layer by layer. The intermediate view image is proposed and synthesized by warping the pixels in an image with the estimated depth and coarse pose. Then, the residual pose transformation can be estimated from the new view image and the image of the adjacent frame to refine the coarse pose. The iterative refinement is implemented in a differentiable manner in this paper, making the whole framework optimized uniformly. Meanwhile, a new image augmentation method is proposed for the pose estimation by synthesizing a new view image, which creatively augments the pose in 3D space but gets a new augmented 2D image. The experiments on KITTI demonstrate that our depth estimation achieves state-of-the-art performance and even surpasses recent approaches that utilize other auxiliary tasks. Our visual odometry outperforms all recent unsupervised monocular learning-based methods and achieves competitive performance to the geometry-based method, ORB-SLAM2 with back-end optimization. Copyright © 2021, The Authors. All rights reserved.

关键词： Robots

An Improved Result on Stabilization of Switched Linear systems with Time-varying Delay ⁎

学校读者我要写书评

暂无评论

IFAC-PapersOnLine 2021年第18期54卷 96-101页

作者： Tan Hou Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 U.S.A.

This paper revisits the stabilization problem of switched linear systems with time-varying delay via state dependent switching strategies. In contrast to the existing works, the commonly adopted stable convex combination assumption is relaxed in this paper. For switched systems satisfying the relaxed assumption, we design a state dependent switching strategy, under which the considered system is asymptotically stable at the origin in the presence of time-varying delay. An optimization problem is formulated to estimate the upper bound of tolerable time delay. Numerical examples are presented to show that our method is applicable to a larger class of switched systems and leads to greater delay bound.

关键词： Asymptotic stability delay bound state dependent switching switched system time-varying delay

Spatial non-locality induced non-markovian EIT in a single giant atom

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Zhu, Y.T. Wu, R.B. Xue, S. Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Department of Automation Tsinghua University Beijing100084 China Beijing National Research Center for Information Science and Technology Beijing100084 China

In recent experiments, electromagnetically induced transparency (EIT) were observed with giant atoms, but nothing unconventional were found from the transmission spectra. In this letter, we show that unconventional EIT does exist in giant atoms, and indicate why it has not been observed so far. Different from these existing works, this letter presents a consistent theory including a real space method and a time delayed master equation for observing unconventional EIT. We discover that this phenomenon is a quantum effect which cannot be correctly described in a semi-classical way as those in recent works. Our theory shows that it can be observed when the time delay between two neighboring coupling points is comparable to the relaxation time of the atom, which is crucial for a future experimental observation. This new phenomenon results from inherent non-locality of the giant atom, which physically forces propagating fields to be standing waves in space and the atom exhibiting retardations in time. Our theory establishes a framework for application of nonlocal systems to quantum information processing. Copyright © 2021, The Authors. All rights reserved.

关键词： Atoms

Network Parameter Generation for One-Shot Object Detection

学校读者我要写书评

暂无评论

Network Parameter Generation for One-Shot Object Detection

2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Wang, Kang Zhao, Jiajia Wang, Yang Zhou, Shuigeng Fudan University Shanghai Key Lab of Intelligent Information Processing School of Computer Science Shanghai200433 China Beijing Electro-Mechanical Engineer Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Nanchang University School of Information Engineering 330031 China

ISBN: (纸本)9781728137926

Recent object detection models have achieved satisfactory performance by deep learning with large-scale annotated datasets. However, these models often perform poorly when the training examples are not sufficient enough, especially for one-shot object detection where there is only one training example of each target class. In this paper, we propose a network parameter generation framework for effective one-shot object detection. By leveraging the semantic relationship between the source-domain and the target-domain (new classes), our framework can generate network parameters for the new classes directly. Furthermore, we develop two implementation schemes for this framework: weighting-based parameter generation and regression-based parameter generation. These two schemes use different information to construct the relationship and transfer knowledge from the source-domain to the target-domain. Experiments on the PASCAL-OSCD benchmark show that our methods can significantly boost the performance of one-shot object detection. © 2019 IEEE.

关键词： Object detection

Demand estimation of water resources based on algorithm comparison

学校读者我要写书评

暂无评论

International Journal of Wireless and Mobile Computing 2019年第2期16卷 110-116页

作者： Wang, Junyan Zhang, Jiangjiang Cai, Xingjuan Ma, Yanyan Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Nanchang330099 China Complex System and Computational Intelligence Laboratory TaiYuan University of Science and Technology Taiyuan003024 China Shanxi Cloud Era TISCO Information Automation Technology Co. Ltd. Taiyuan030003 China

Water is the source of life and the correct assessment of water resources is an important prerequisite for the rational utilisation of water resources. In this paper, water resources are evaluated and predicted by three different algorithms, including Bat Algorithm (BA), Particle Swarm Optimisation (PSO) and Pigeon-Inspired Optimisation (PIO). Comparing the errors of water resources assessed for the three algorithms, we select an algorithm of the minimum error to predict the future water demand. In the experiments, firstly, the water data from 2003 to 2012 are used to find the optimal weights of the models. Then, the weight factor is combined with the given model to gain the error between predicted value and the remaining data (2013–2015). Finally, the simulation results show that PIO algorithm has a better performance compared with the BA and PSO algorithms. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Water resources

Deep Rank-Consistent Pyramid Model for Enhanced Crowd Counting

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Gao, Jiaqi Huang, Zhizhong Lei, Yiming Shan, Hongming Wang, James Z. Wang, Fei-Yue Zhang, Junping The Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China The Institute of Science and Technology for Brain-inspired Intelligence MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China The Shanghai Center for Brain Science and Brain-Inspired Technology Shanghai201210 China The College of Information Sciences and Technology The Pennsylvania State University University ParkPA16802 United States The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The Institute of Systems Engineering Macau University of Science and Technology China Qingdao Academy of Intelligent Industries Qingdao266109 China

Most conventional crowd counting methods utilize a fully-supervised learning framework to establish a mapping between scene images and crowd density maps. They usually rely on a large quantity of costly and time-intensive pixel-level annotations for training supervision. One way to mitigate the intensive labeling effort and improve counting accuracy is to leverage large amounts of unlabeled images. This is attributed to the inherent self-structural information and rank consistency within a single image, offering additional qualitative relation supervision during training. Contrary to earlier methods that utilized the rank relations at the original image level, we explore such rank-consistency relation within the latent feature spaces. This approach enables the incorporation of numerous pyramid partial orders, strengthening the model representation capability. A notable advantage is that it can also increase the utilization ratio of unlabeled samples. Specifically, we propose a Deep Rank-consistEnt pyrAmid Model (DREAM), which makes full use of rank consistency across coarse-to-fine pyramid features in latent spaces for enhanced crowd counting with massive unlabeled images. In addition, we have collected a new unlabeled crowd counting dataset, FUDAN-UCC, comprising 4,000 images for training purposes. Extensive experiments on four benchmark datasets, namely UCF-QNRF, ShanghaiTech PartA and PartB, and UCF-CC-50, show the effectiveness of our method compared with previous semi-supervised methods. The codes are available at https://***/bridgeqiqi/DREAM. Copyright © 2022, The Authors. All rights reserved.

关键词： Image enhancement

Path Planning and Evaluation for Obstacle Avoidance of Manipulator Based on Improved Artificial Potential Field and Danger Field

学校读者我要写书评

暂无评论

Path Planning and Evaluation for Obstacle Avoidance of Manip...

第33届中国控制与决策会议

作者： Jiangbo Zhao Qiang Zhao Junzheng Wang Xin Zhang Yanlong Wang Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of Technology Technical center Xinxing Cathay International Group Co.Ltd. Technology Center of Special Vehicle Manufacture and Evaluation Enginneering of Beijing Beijing North Vehicle Group Co.Ltd.

This paper takes 6-DOF manipulator as the research object,proposes the improved Artificial Potential Field(APF) method to plan the obstacle avoidance path of the manipulator,and combines the Danger Field(DF) method to evaluate the safety of the path planned using *** to the characteristics of the manipulator,the kinematics model of the manipulator is analyzed,and the ball envelope algorithm is applied to simplify the physical model of the *** with the traditional APF method,the improved APF searches in the joint space and introduces the joint attraction potential to improve the search speed and *** problem of local minimum is dealt with by the combination of adding virtual obstacles and increasing joint attraction *** improved APF not only has the advantages of good real-time performance and smooth path,but also solves the problem of the traditional APF falling into a local minimum,and combines the danger field method to judge the path rationality to ensure no collision with *** simulation verification,the proposed method realizes the obstacle avoidance path planning of the manipulator and the safety evaluation of the planned path.

关键词： Artificial potential field Danger field Obstacle avoidance Path planning Collision detection

Local Path Planning Algorithm for UGV Based on Improved Covariance Matrix Adaptive Evolution Strategy

学校读者我要写书评

暂无评论

Local Path Planning Algorithm for UGV Based on Improved Cova...

第33届中国控制与决策会议

作者： Jiangbo Zhao Jiaquan Zhang Junzheng Wang Xin Zhang Yanlong Wang Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of Technology Technical center Xinxing Cathay International Group Co.Ltd. Techenology Center of Special Vehicle Manufacture and Evaluation Engineering of Beijing Beijing North Vehicle Group Co.Ltd.

Local path planning algorithm is one of the key technologies for unmanned ground vehicle(UGV).In order to reduce the computational complexity of the local path planning algorithm and ensure the real-time performance of the algorithm,a non-uniform column grid lines modeling method is introduced,and on this basis,a modeling method for planning paths is *** at the path planning problem in a multi-obstacle environment,the evaluation function of the path is constructed from four aspects,and the covariance matrix adaptive evolution strategy(CMA-ES)is used to solve the nonlinear optimization *** order to further reduce the amount of calculation,the CMA-ES algorithm is improved by the dynamic adjustment strategy of population *** results show that the path planning algorithm can effectively realize the local path planning in complex environment.

关键词： Local path planning CMA-ES Unmanned ground vehicle

Impulse control of chaos in the exible shaft rotating-lifting system of the mono-silicon crystal puller

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Zhou, Zi-Xuan Grebogi, Celso Ren, Hai-Peng Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an Shaanxi710048 China North Minzu University Library Yinchuan Ningxia750021 China Institute for Complex System and Mathematical Biology University of Aberdeen AB24 3UE United Kingdom

Chaos is shown to occur in the flexible shaft rotating-lifting (FSRL) system of the mono-silicon crystal puller. Chaos is, however, harmful for the quality of mono-silicon crystal production. Therefore, it should be suppressed. Many chaos control methods have been proposed theoretically and some have even been used in applications. For a practical plant displaying harmful chaos, engineers from a specified area usually face with the challenge to identifying chaos and to suppressing it by using a proper method. However, despite of the existing methods, chaos control method selection in the FSRL system is not a trivial task. For example, for the OGY method, if one cannot find a practical adjustable parameter, then the OGY method cannot be applied. An impulsive control method is being proposed which is efficiently able to suppress chaos in the FSRL system. The selection of the control parameters is obtained by using the Melnikov method. Simulation results show the correctness of our theoretical analysis and the effectiveness of the proposed chaos control method. Copyright © 2020, The Authors. All rights reserved.

关键词： Silicon