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检索条件"机构=Advanced Robotics and Intelligent Systems Laboratory & Control and Intelligent Processing Center"
342 条 记 录,以下是301-310 订阅
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BoostTree and BoostForest for Ensemble Learning
arXiv
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arXiv 2020年
作者: Zhao, Changming Wu, Dongrui Huang, Jian Yuan, Ye Zhang, Hai-Tao Peng, Ruimin Shi, Zhenhua Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China The Autonomous Intelligence Unmanned Systems Engineering Research Center of Ministry of Education of China The State Key Lab of Digital Manufacturing Equipment and Technology Wuhan China
Bootstrap aggregating (Bagging) and boosting are two popular ensemble learning approaches, which combine multiple base learners to generate a composite model for more accurate and more reliable performance. They have ... 详细信息
来源: 评论
Deep Rank-Consistent Pyramid Model for Enhanced Crowd Counting
arXiv
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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-inten... 详细信息
来源: 评论
Enhanced Visual Feedback with Decoupled Viewpoint control in Immersive Humanoid Robot Teleoperation using SLAM
Enhanced Visual Feedback with Decoupled Viewpoint Control in...
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IEEE-RAS International Conference on Humanoid Robots
作者: Yang Chen Leyuan Sun Mehdi Benallegue Rafael Cisneros-Limón Rohan P. Singh Kenji Kaneko Arnaud Tanguy Guillaume Caron Kenji Suzuki Abderrahmane Kheddar Fumio Kanehiro School of Integrative and Global Majors (SIGMA) University of Tsukuba Japan CNRS-AIST JRL (Joint Robotics Laboratory) IRL National Institute of Advanced Industrial Science and Technology (AIST) Department of Intelligent and Mechanical Interaction Systems Graduate School of Science and Technology University of Tsukuba Japan MIS lab Universite de Picardie Jules Verne Amiens France Faculty of Engineering and Center for Cybernetics Research University of Tsukuba Japan
In immersive humanoid robot teleoperation, there are three main shortcomings that can alter the transparency of the visual feedback: (i) the lag between the motion of the operator's and robot's head due to net... 详细信息
来源: 评论
Urban Digital Twins for intelligent Road Inspection
Urban Digital Twins for Intelligent Road Inspection
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IEEE International Conference on Big Data
作者: Rui Fan Yikang Zhang Sicen Guo Jiahang Li Yi Feng Shuai Su Yanting Zhang Wenshuo Wang Yu Jiang Mohammud Junaid Bocus Xingyi Zhu Qijun Chen the Department of Control Science & Engineering Frontiers Science Center for Intelligent Autonomous Systems and State Key Laboratory of Intelligent Autonomous Systems Robotics & Artificial Intelligence Laboratory (RAIL) Tongji University Shanghai P. R. China Department of Computer Science & Technology Donghua University Shanghai P. R. China Department of Civil Engineering McGill University Montreal Canada CTO office at ClearMotion Billerica MA USA Department of Electrical & Electronic Engineering the University of Bristol BS8 1UB U.K Key Laboratory of Road and Traffic Engineering of Ministry of Education Tongji University Shanghai P. R. China
Urban digital twin (UDT) technologies offer new opportunities for intelligent road inspection (IRI). This paper first reviews the state-of-the-art algorithms used in the two key components of UDT-based IRI systems: (1... 详细信息
来源: 评论
LinK3D: Linear Keypoints Representation for 3D LiDAR Point Cloud
arXiv
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arXiv 2022年
作者: Cui, Yunge Zhang, Yinlong Dong, Jiahua Sun, Haibo Chen, Xieyuanli Zhu, Feng The Key Laboratory of Opto-Electronic Information Processing Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China The Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China The State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Shenyang China The Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China The University of Chinese Academy of Sciences Beijing101408 China The Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China The College of Intelligence Science and Technology National University of Defense Technology Changsha China
Feature extraction and matching are the basic parts of many robotic vision tasks, such as 2D or 3D object detection, recognition, and registration. As is known, 2D feature extraction and matching have already achieved... 详细信息
来源: 评论
Effective Throughput Optimization of SAG Milling Process Based on BPNN and Genetic Algorithm
Effective Throughput Optimization of SAG Milling Process Bas...
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Industrial Cyber-Physical systems (ICPS)
作者: Zhenhong Liao Ce Xu Wen Chen Qifu Chen Feng Wang Jinhua She 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 Department of Mineral Resources Development and Utilization Changsha Research Institute of Mining and Metallurgy CO. LTD. Chagnsha China Hunan Valin Lianyuan Iron And Steel Co. Ltd. Loudi China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan
Grinding is an energy-consuming process in mineral processing industry. Improving grinding processing capacity per unit power consumption is an effective means to reduce grinding production cost. In this paper, a new ... 详细信息
来源: 评论
PrePARE: Predictive Proprioception for Agile Failure Event Detection in Robotic Exploration of Extreme Terrains
arXiv
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arXiv 2022年
作者: Dey, Sharmita Fan, David Schmid, Robin Dixit, Anushri Otsu, Kyohei Touma, Thomas Schilling, Arndt F. Agha-Mohammadi, Ali-Akbar NASA Jet Propulsion Laboratory California Institute of Technology PasadenaCA United States The University of Goettingen University Medical Center Goettingen Germany The Institute for Robotics and Intelligent Machines Georgia Institute of Technology AtlantaGA United States Zurich8092 Switzerland Control and Dynamical Systems California Institute of Technology PasadenaCA United States Mechanical and Civil Engineering California Institute of Technology PasadenaCA United States
Legged robots can traverse a wide variety of terrains, some of which may be challenging for wheeled robots, such as stairs or highly uneven surfaces. However, quadruped robots face stability challenges on slippery sur... 详细信息
来源: 评论
Gait Phase Classification Based on sEMG Signals Using Long Short-Term Memory for Lower Limb Exoskeleton Robot
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IOP Conference Series: Materials Science and Engineering 2020年 第1期853卷
作者: Ye Yuan Ziming Guo Can Wang Shengcai Duan Lufeng Zhang Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergic Systems Shenzhen Institutes of Advanced Technology Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University.
In this work, we present a Long Short-Term Memory Model (LSTMM) for gait phase classification based on sEMG signals to control the lower limb exoskeleton robot which can recognize 2 phases (Stand and Swing) of leg pha...
来源: 评论
Barrier-certified adaptive reinforcement learning with applications to brushbot navigation
arXiv
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arXiv 2018年
作者: Ohnishi, Motoya Wang, Li Notomista, Gennaro Egerstedt, Magnus School of Electrical Engineering Royal Institute of Technology Stockholm11428 Sweden Georgia Robotics and Intelligent Systems Laboratory Georgia Institute of Technology AtlantaGA30332 United States RIKEN Center for Advanced Intelligence Project Tokyo103-0027 Japan School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States School of Mechanical Engineering Georgia Institute of Technology AtlantaGA30313 United States
This paper presents a safe learning framework that employs an adaptive model learning algorithm together with barrier certificates for systems with possibly nonstationary agent dynamics. To extract the dynamic structu... 详细信息
来源: 评论
Convolutional ordinal regression forest for image ordinal estimation
arXiv
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arXiv 2020年
作者: Zhu, Haiping Shan, Hongming Zhang, Yuheng Che, Lingfu Xu, Xiaoyang Zhang, Junping Shi, Jianbo Wang, Fei-Yue 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 GRASP Laboratory University of Pennsylvania PhiladelphiaPA United States The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The Institute of Systems Engineering Macau University of Science and Technology 999078 China The University of Chinese Academy of Sciences Beijing100049 China
Image ordinal estimation is to predict the ordinal label of a given image, which can be categorized as an ordinal regression problem. Recent methods formulate an ordinal regression problem as a series of binary classi... 详细信息
来源: 评论