咨询与建议

限定检索结果

文献类型

  • 212 篇 期刊文献
  • 9 篇 会议

馆藏范围

  • 221 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 221 篇 工学
    • 215 篇 控制科学与工程
    • 209 篇 电气工程
    • 13 篇 计算机科学与技术...
    • 1 篇 机械工程
    • 1 篇 信息与通信工程
    • 1 篇 软件工程
  • 6 篇 管理学
    • 6 篇 管理科学与工程(可...
  • 1 篇 医学
    • 1 篇 基础医学(可授医学...

主题

  • 221 篇 deep learning in...
  • 23 篇 visual learning
  • 20 篇 perception for g...
  • 19 篇 task analysis
  • 18 篇 motion and path ...
  • 18 篇 localization
  • 18 篇 computer vision ...
  • 16 篇 visual-based nav...
  • 16 篇 robots
  • 15 篇 object detection
  • 14 篇 segmentation and...
  • 14 篇 semantic scene u...
  • 12 篇 computer vision ...
  • 12 篇 training
  • 11 篇 learning from de...
  • 11 篇 force and tactil...
  • 11 篇 learning and ada...
  • 11 篇 slam
  • 10 篇 grasping
  • 9 篇 robot sensing sy...

机构

  • 6 篇 hong kong univ s...
  • 5 篇 univ michigan de...
  • 5 篇 georgia inst tec...
  • 5 篇 univ perugia dep...
  • 4 篇 imperial coll lo...
  • 4 篇 stanford univ st...
  • 4 篇 natl univ singap...
  • 3 篇 swiss fed inst t...
  • 3 篇 univ hong kong d...
  • 3 篇 carnegie mellon ...
  • 3 篇 city univ hong k...
  • 3 篇 kth royal inst t...
  • 3 篇 univ michigan de...
  • 2 篇 seoul natl univ ...
  • 2 篇 univ adelaide sc...
  • 2 篇 georgia inst tec...
  • 2 篇 mit comp sci & a...
  • 2 篇 karlsruhe inst t...
  • 2 篇 swiss fed inst t...
  • 2 篇 carnegie mellon ...

作者

  • 8 篇 liu ming
  • 5 篇 costante gabriel...
  • 5 篇 yang guang-zhong
  • 5 篇 bohg jeannette
  • 5 篇 calandra roberto
  • 5 篇 johnson-roberson...
  • 3 篇 kumar vijay
  • 3 篇 chen steven w.
  • 3 篇 sartoretti guill...
  • 3 篇 tai lei
  • 3 篇 rus daniela
  • 3 篇 zhou xiao-yun
  • 3 篇 pan jia
  • 3 篇 vasudevan ram
  • 3 篇 davison andrew j...
  • 3 篇 choi changhyun
  • 3 篇 folkesson john
  • 3 篇 kelly jonathan
  • 3 篇 kawai hisashi
  • 3 篇 magassouba aly

语言

  • 221 篇 英文
检索条件"主题词=deep learning in robotics and automation"
221 条 记 录,以下是81-90 订阅
排序:
GOSELO: Goal-Directed Obstacle and Self-Location Map for Robot Navigation Using Reactive Neural Networks
收藏 引用
IEEE robotics AND automation LETTERS 2018年 第2期3卷 696-703页
作者: Kanezaki, Asako Nitta, Jirou Sasaki, Yoko Natl Inst Adv Ind Sci & Technol Tokyo 1350064 Japan
Robot navigation using deep neural networks has been drawing a great deal of attention. Although reactive neural networks easily learn expert behaviors and are computationally efficient, they suffer from generalizatio... 详细信息
来源: 评论
TACTO: A Fast, Flexible, and Open-Source Simulator for High-Resolution Vision-Based Tactile Sensors
收藏 引用
IEEE robotics AND automation LETTERS 2022年 第2期7卷 3930-3937页
作者: Wang, Shaoxiong Lambeta, Mike Chou, Po-Wei Calandra, Roberto Meta AI Menlo Pk CA 94025 USA MIT Cambridge MA 02139 USA
Simulators perform an important role in prototyping, debugging, and benchmarking new advances in robotics and learning for control. Although many physics engines exist, some aspects of the real world are harder than o... 详细信息
来源: 评论
learning to See the Wood for the Trees: deep Laser Localization in Urban and Natural Environments on a CPU
收藏 引用
IEEE robotics AND automation LETTERS 2019年 第2期4卷 1327-1334页
作者: Tinchev, Georgi Penate-Sanchez, Adrian Fallon, Maurice Univ Oxford Oxford Robot Inst Dynam Syst Grp Oxford OX2 6NN England
Localization in challenging, natural environments, such as forests or woodlands, is an important capability for many applications from guiding a robot navigating along a forest trail to monitoring vegetation growth wi... 详细信息
来源: 评论
Real-Time 3-D Shape Instantiation From Single Fluoroscopy Projection for Fenestrated Stent Graft Deployment
收藏 引用
IEEE robotics AND automation LETTERS 2018年 第2期3卷 1314-1321页
作者: Zhou, Xiao-Yun Lin, Jianyu Riga, Celia Yang, Guang-Zhong Lee, Su-Lin Imperial Coll London Hamlyn Ctr Robot Surg London SW7 2AZ England St Marys Hosp Reg Vasc Unit London W2 1NY England Imperial Coll London Acad Div Surg London SW7 2AZ England
Robot-assisted deployment of fenestrated stent grafts in fenestrated endovascular aortic repair (FEVAR) requires accurate geometrical alignment. Currently, this process is guided by two-dimensional (2-D) fluoroscopy, ... 详细信息
来源: 评论
Generative Localization With Uncertainty Estimation Through Video-CT Data for Bronchoscopic Biopsy
收藏 引用
IEEE robotics AND automation LETTERS 2020年 第1期5卷 258-265页
作者: Zhao, Cheng Shen, Mali Sun, Li Yang, Guang-Zhong Imperial Coll London Hamlyn Ctr London SW7 2AZ England Univ Oxford Oxford Robot Inst Oxford OX1 2JD England Shanghai Jiao Tong Univ Inst Med Shanghai 200240 Peoples R China
Robot-assisted endobronchial intervention requires accurate localization based on both intra- and pre-operative data. Most existing methods achieve this by registering 2D videos with 3D CT models according to a define... 详细信息
来源: 评论
deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution
收藏 引用
IEEE robotics AND automation LETTERS 2018年 第4期3卷 4007-4014页
作者: Rothfuss, Jonas Ferreira, Fabio Aksoy, Eren Erdal Zhou, You Asfour, Tamim Karlsruhe Inst Technol Inst Anthropomat & Robot D-76131 Karlsruhe Germany Halmstad Univ Sch Informat Technol S-30118 Halmstad Sweden
We present a novel deep neural network architecture for representing robot experiences in an episodic-like memory that facilitates encoding, recalling, and predicting action experiences. Our proposed unsupervised deep... 详细信息
来源: 评论
Distributed Perception by Collaborative Robots
收藏 引用
IEEE robotics AND automation LETTERS 2018年 第4期3卷 3709-3716页
作者: Hadidi, Ramyad Cao, Jiashen Woodward, Matthew Ryoo, Michael S. Kim, Hyesoon Georgia Inst Technol Sch Comp Sci Atlanta GA 30332 USA Georgia Inst Technol Dept Elect Engn Atlanta GA 30332 USA EgoVid Inc Ulsan 44919 South Korea
Recognition ability and, more broadly, machine learning techniques enable robots to perform complex tasks and allow them to function in diverse situations. In fact, robots can easily access an abundance of sensor data... 详细信息
来源: 评论
PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent learning
收藏 引用
IEEE robotics AND automation LETTERS 2019年 第3期4卷 2378-2385页
作者: Sartoretti, Guillaume Kerr, Justin Shi, YunFei Wagner, Glenn Kumar, T. K. Satish Koenig, Sven Choset, Howie Carnegie Mellon Univ Robot Inst Pittsburgh PA 15213 USA CSIRO Pullenvale Qld 4069 Australia Univ Southern Calif Comp Sci Dept Los Angeles CA 90089 USA
Multi-agent path finding (MAPF) is an essential component of many large-scale, real-world robot deployments, from aerial swarms to warehouse automation. However, despite the community's continued efforts, most sta... 详细信息
来源: 评论
Recurrent-OctoMap: learning State-Based Map Refinement for Long-Term Semantic Mapping With 3-D-Lidar Data
收藏 引用
IEEE robotics AND automation LETTERS 2018年 第4期3卷 3749-3756页
作者: Sun, Li Yan, Zhi Zaganidis, Anestis Zhao, Cheng Duckett, Tom Univ Lincoln L CAS Lincoln LN6 7TS England UTBM Lab Elect Informat & Image CNRS F-90010 Belfort France
This letter presents a novel semantic mapping approach, Recurrent-OctoMap, learned from long-term three-dimensional (3-D) Lidar data. Most existing semantic mapping approaches focus on improving semantic understanding... 详细信息
来源: 评论
Lifelong Federated Reinforcement learning: A learning Architecture for Navigation in Cloud Robotic Systems
收藏 引用
IEEE robotics AND automation LETTERS 2019年 第4期4卷 4555-4562页
作者: Liu, Boyi Wang, Lujia Liu, Ming Chinese Acad Sci Shenzhen Inst Adv Technol Cloud Comp Lab Shenzhen 518055 Peoples R China Univ Chinese Acad Sci Beijing 100190 Peoples R China Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Peoples R China
This letter was motivated by the problem of how to make robots fuse and transfer their experience so that they can effectively use prior knowledge and quickly adapt to new environments. To address the problem, we pres... 详细信息
来源: 评论