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Institution

Willow Garage

About: Willow Garage is a based out in . It is known for research contribution in the topics: Robot & Mobile robot. The organization has 76 authors who have published 191 publications receiving 28617 citations.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University’s Department of Computer Science, was pleased to present the 2012 Spring Symposium Series, held Monday through Wednesday, March 26–28, 2012 at Stanford University.
Abstract: The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University’s Department of Computer Science, was pleased to present the 2012 Spring Symposium Series, held Monday through Wednesday, March 26–28, 2012 at Stanford University, Stanford, California USA. The six symposia held were AI, The Fundamental Social Aggregation Challenge (cochaired by W. F. Lawless, Don Sofge, Mark Klein, and Laurent Chaudron); Designing Intelligent Robots (cochaired by George Konidaris, Byron Boots, Stephen Hart, Todd Hester, Sarah Osentoski, and David Wingate); Game Theory for Security, Sustainability, and Health (cochaired by Bo An and Manish Jain); Intelligent Web Services Meet Social Computing (cochaired by Tomas Vitvar, Harith Alani, and David Martin); Self-Tracking and Collective Intelligence for Personal Wellness (cochaired by Takashi Kido and Keiki Takadama); and Wisdom of the Crowd (cochaired by Caroline Pantofaru, Sonia Chernova, and Alex Sorokin). The papers of the six symposia were published in the AAAI technical report series.

1 citations

Proceedings ArticleDOI
29 Feb 2012
TL;DR: This hands-on workshop will introduce ROS and showcase two pilot courses taught using ROS and the Kinect and develop Python programs on low-cost Kinect-equipped robots and the ARDrone quadcopter.
Abstract: The Microsoft Kinect and Willow Garage's Robot Operating System (ROS) are changing the way robots are developed. Together, these tools can enable today's CS educators to provide richer and more research-representative experiences with robots and perception. This hands-on workshop will introduce ROS and showcase two pilot courses taught using ROS and the Kinect. Four 20-minute talks will intersperse with participants' hands-on development of Python programs on low-cost Kinect-equipped robots and the ARDrone quadcopter. This workshop is intended for all college-level CS educators interested in robotics or embodied AI. First-time ROS/Kinect users are particularly welcome! Laptops and robots will be provided. See http://www.ros.org/wiki/Courses/sigcse2012. Laptops optional.

1 citations

Proceedings Article
01 Jan 2008
TL;DR: This paper describes a computationally efficient approach to identifying and following footpaths, using only a single camera, that takes the robot’s kinematics into consideration when planning the best trajectory to follow the path that it is on.
Abstract: The ability to follow man-made paths and roads is an important capability for a number of robotic tasks. To operate in outdoor environments designed for humans, autonomous robots must identify footpaths, and drive along them. In this paper, we describe a computationally efficient approach to identifying and following footpaths, using only a single camera. Our technique takes the robot’s kinematics into consideration when planning the best trajectory to follow the path that it is on. We show that our approach is highly robust to visual artifacts such as shadows, lighting changes, ground texture changes, and occlusions.
Proceedings Article
01 Jan 2010
TL;DR: A hierarchical planning system that finds high-quality kinematic solutions to task-level problems and takes advantage of subtask-specific irrelevance information, reusing optimal solutions to state-abstracted subproblems across the search space.
Abstract: We describe a hierarchical planning system and its application to robotic manipulation. The novel features of the system are: 1) it finds high-quality kinematic solutions to task-level problems; 2) it takes advantage of subtask-specific irrelevance information, reusing optimal solutions to state-abstracted subproblems across the search space. We also discuss ongoing work to speed up the system, by exploiting "angelic" approximate models of the high-level actions involved.

Authors

Showing all 76 results

NameH-indexPapersCitations
Ian Goodfellow85137135390
Kurt Konolige6417124749
Andreas Paepcke501409405
Gunter Niemeyer4715317135
Radu Bogdan Rusu439715008
Mike J. Dixon421828272
Gary Bradski418223763
Leila Takayama34904549
Sachin Chitta34564589
Wendy Ju341843861
Maya Cakmak341114452
Brian P. Gerkey32517923
Caroline Pantofaru26654116
Matei Ciocarlie25913176
Kaijen Hsiao24292366
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20172
20164
20152
201414
201336
201239