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检索条件"主题词=deep learning in robotics and automation"
221 条 记 录,以下是101-110 订阅
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Localization of Inspection Device Along Belt Conveyors With Multiple Branches Using deep Neural Networks
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IEEE robotics AND automation LETTERS 2020年 第2期5卷 2921-2928页
作者: Yasutomi, Andre Yuji Enoki, Hideo Hitachi Ltd Robot Res Dept Ctr Technol Innovat Mech Engn Res & Dev Grp Hitachinaka Ibaraki 3120034 Japan
Regular inspections of belt conveyors are required to prevent the damage of transported objects. Nevertheless, inspections can be troublesome for belt conveyors composed of a plurality of belt lines with multiple bran... 详细信息
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learning to Assemble: Estimating 6D Poses for Robotic Object-Object Manipulation
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IEEE robotics AND automation LETTERS 2020年 第2期5卷 1159-1166页
作者: Stevsic, Stefan Christen, Sammy Hilliges, Otmar Swiss Fed Inst Technol Dept Comp Sci Adv Interact Technol Lab CH-8092 Zurich Switzerland
In this letter we propose a robotic vision task with the goal of enabling robots to execute complex assembly tasks in unstructured environments using a camera as the primary sensing device. We formulate the task as an... 详细信息
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deepGait: Planning and Control of Quadrupedal Gaits Using deep Reinforcement learning
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IEEE robotics AND automation LETTERS 2020年 第2期5卷 3699-3706页
作者: Tsounis, Vassilios Alge, Mitja Lee, Joonho Farshidian, Farbod Hutter, Marco Swiss Fed Inst Technol Robot Syst Lab CH-8092 Zurich Switzerland
This letter addresses the problem of legged locomotion in non-flat terrain. As legged robots such as quadrupeds are to be deployed in terrains with geometries which are difficult to model and predict, the need arises ... 详细信息
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Geometrically Mappable Image Features
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IEEE robotics AND automation LETTERS 2020年 第2期5卷 2062-2069页
作者: Thoma, Janine Paudel, Danda Pani Chhatkuli, Ajad Gool, Luc Van ETH Comp Vis Lab CH-8092 Zurich Switzerland Katholieke Univ Leuven B-3000 Leuven Belgium
Vision-based localization of an agent in a map is an important problem in robotics and computer vision. In that context, localization by learning matchable image features is gaining popularity due to recent advances i... 详细信息
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CorsNet: 3D Point Cloud Registration by deep Neural Network
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IEEE robotics AND automation LETTERS 2020年 第3期5卷 3960-3966页
作者: Kurobe, Akiyoshi Sekikawa, Yusuke Ishikawa, Kohta Saito, Hideo Keio Univ Dept Sci & Technol Yokohama Kanagawa 2238522 Japan Denso IT Lab Inc Tokyo 1500002 Japan
Point cloud registration is a key problem for robotics and computer vision communities. This represents estimating a rigid transform which aligns one point cloud to another. Iterative closest point (ICP) is a well-kno... 详细信息
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Low to High Dimensional Modality Hallucination Using Aggregated Fields of View
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IEEE robotics AND automation LETTERS 2020年 第2期5卷 1983-1990页
作者: Gunasekar, Kausic Qiu, Qiang Yang, Yezhou Arizona State Univ Tempe AZ 85281 USA Duke Univ Durham NC 27708 USA
Real-world robotics systems deal with data from a multitude of modalities, especially for tasks such as navigation and recognition. The performance of those systems can drastically degrade when one or more modalities ... 详细信息
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Robot Navigation in Crowds by Graph Convolutional Networks With Attention Learned From Human Gaze
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IEEE robotics AND automation LETTERS 2020年 第2期5卷 2754-2761页
作者: Chen, Yuying Liu, Congcong Shi, Bertram E. Liu, Ming Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Peoples R China
Safe and efficient crowd navigation for mobile robot is a crucial yet challenging task. Previous work has shown the power of deep reinforcement learning frameworks to train efficient policies. However, their performan... 详细信息
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Depth Based Semantic Scene Completion With Position Importance Aware Loss
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IEEE robotics AND automation LETTERS 2020年 第1期5卷 219-226页
作者: Li, Jie Liu, Yu Yuan, Xia Zhao, Chunxia Siegwart, Roland Reid, Ian Cadena, Cesar Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing 210094 Jiangsu Peoples R China Univ Adelaide Sch Comp Sci Adelaide SA 5005 Australia Swiss Fed Inst Technol Autonomous Syst Lab CH-8092 Zurich Switzerland
Semantic scene completion (SSC) refers to the task of inferring the 3D semantic segmentation of a scene while simultaneously completing the 3D shapes. We propose PALNet, a novel hybrid network for SSC based on single ... 详细信息
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Motor Synergy Development in High-Performing deep Reinforcement learning Algorithms
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IEEE robotics AND automation LETTERS 2020年 第2期5卷 1271-1278页
作者: Chai, Jiazheng Hayashibe, Mitsuhiro Tohoku Univ Grad Sch Engn Dept Robot Neurorobot Lab Sendai Miyagi 9808579 Japan
As human motor learning is hypothesized to use the motor synergy concept, we investigate if this concept could also be observed in deep reinforcement learning for robotics. From this point of view, we carried out a jo... 详细信息
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learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes
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IEEE robotics AND automation LETTERS 2020年 第2期5卷 1032-1038页
作者: Marchal, Nicolas Moraldo, Charlotte Blum, Hermann Siegwart, Roland Cadena, Cesar Gawel, Abel Swiss Fed Inst Technol Autonomous Syst Lab CH-8092 Zurich Switzerland
deep learning has enabled remarkable advances in scene understanding, particularly in semantic segmentation tasks. Yet, current state of the art approaches are limited to a closed set of classes, and fail when facing ... 详细信息
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