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Pose / Object recognition / Robot / ROS / Care-Providing Robot FRIEND / Computer vision / Robotics / Artificial intelligence


Cloud-Based Robot Grasping with the Google Object Recognition Engine Ben Kehoe1 Akihiro Matsukawa2
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Document Date: 2013-02-25 00:51:23


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File Size: 1,91 MB

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City

New Delhi / Mountain View / Marseille / Florence / Adaptive Cloud / Barcelona / Berlin / Nashville / /

Company

Training Set Size / F.F. Kong A.S. / MIT Press / Autonomous Decentralized Systems / Amazon / Google / Rate Training Time / Microsoft / /

Country

India / Germany / Italy / United States / Spain / /

Currency

USD / /

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Event

Product Recall / Product Issues / /

Facility

University GraspIt / University of California / Amphitheatre Parkway / Point Cloud Library / generated using the Columbia University GraspIt / /

IndustryTerm

large-scale object recognition server / household products / internet resources / web links / surface reconstruction tools / Internet Technology / Online pose estimation / alignment solutions / online phase / computing / Online Robots / object recognition server / automation systems / cloud server / Web-Based Tool / Web Architecture / opensource software / pose estimation algorithm / object recognition systems / parallel grid computing / wireless networking / /

MarketIndex

SET 100 / /

OperatingSystem

OSE / Android / /

Organization

Columbia University / IEEE Society of Robotics / Center of Mass / National Science Foundation / MIT / University of California / Berkeley / Department of Electrical Engineering and Computer Science / Department of Mechanical Engineering / Robotics and Automation Technical Committee on Networked Robotics / Department of Industrial Engineering and Operations Research / Robot Cloud Center / EECS Department / /

Person

Rajesh Arumugam / V / A. Saxena / Dave Ferguson / Sachin Patil / Lumin Zhang / Florent Perronnin / George Stockman / Steve Gentner / Antonio Torralba / Yang Hua / Weiqiang Yang / Matei Ciocarlie / Justin Driemeyer / R.B. Rusu / Pieter Abbeel / David McAllester / Shuicheng Yan / Kevin P. Murphy / Arshan Poursohi / Ben Kehoe / Chaitanya Gharpure / Andrew Y. Ng / Arjun Baokar / Carl Sutter / Grasps Humans / Luis von Ahn / Kaijen Hsiao / Qiang Chen / Jeff Wiegley / Cordelia Schmid / Thomas Mensink / Siddhartha S. Srinivasa / Bogdan Rusu / Eric Guizzo / Matthijs Douze / Zhihui Du / Alexander Sorokin / James J. Kuffner / Dmitry Berenson / Yinong Chen / Michael Isard / Herve Jegou / Deva Ramanan / William T. Freeman / Richard N. Taylor / David Forsyth / Zoe McCarthy / Jakob Verbeek / Xin Sun / Ross B Girshick / Josef Sivic / Bryan C. Russell / Michael Mascha / Nick Rothenberg / Andrew Zisserman / Richard Szeliski / James Philbin / Ethan Dreyfuss / Ken Goldberg / I.A. Sucan / Dominique Hunziker / Chen Xu / Roland Siegwart / Caroline Pantofaru / Alvaro Collet / Pedro F Felzenszwalb / Grasp Set / Xiaoying Wang / Peter Brook / Sachin Chitta / Gabriela Csurka / Markus Waibel / Gary Bradski / Zhongyang Huang / Ondrej Chum / Zheng Song / /

Position

representative / planner / inverse kinematics planner / Candidate / /

Product

iPhone / Rate Training / Training Set Size / PR2 / rate / /

ProgrammingLanguage

Java / /

ProvinceOrState

California / Tennessee / /

PublishedMedium

The International Journal / /

Technology

3-D / Internet Technology / previous sampling-based algorithm / Java / CAD / ICP algorithm / smartphone / machine learning / Android / Image Processing / pose estimation algorithm / smartphones / HTTP / Digital Imaging / /

URL

http /

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