I strongly believe that in order to create a benchmark for robotics we need a standard at the level of programming. Robotics developers prefer ROS as the...
Through my PhD on Deep Learning based robotics, I read a lot of papers on Machine Learning, Reinforcement Learning and AI in general. But papers can be a bit...
Robohub is a non-profit online communication platform that brings together experts in robotics research, start-ups, business, and education from around the world.
Humans easily outperform machines when it comes to tightening and loosening screw fasteners. The future of manufacturing and recycling may depend on changing that.
Proceedings of the 1st Annual Conference on Robot Learning on 13-15 November 2017 Published as Volume 78 by the Proceedings of Machine Learning Research on 18 October 2017. Volume Edited by: Sergey Levine Vincent Vanhoucke Ken Goldberg Series Editors: Neil D. Lawrence Mark Reid
This expands the range of procedures surgical robots can be involved in, and thus the size of the market. Da Vinci itself has four arms, three of which...
In the first episode of Humans+, Motherboard dives into the world of future prosthetics, and the people working on closing the gap between man and machine. W...
RoboDK is a powerful offline simulator for industrial robots. This video shows how to create and simulate a robot program using Python. For more information...
RoboDK software integrates robot simulation and offline programming for industrial robots. Deliver solutions for any industrial application, from robot machining applications to pick and place. Prepare your simulation in a matter of minutes!
This tutorial is an introduction to using Moveit!. it covers how to configure the robot arm as well as how to attach it to the robot local frame. additionall...
G. Schreiber, A. Stemmer, and R. Bischoff. IEEE Workshop on Innovative Robot Control Architectures for Demanding (Research) Applications How to Modify and Enhance Commercial Controllers (ICRA 2010), page 15--21. Citeseer, (2010)
S. Levine, P. Pastor, A. Krizhevsky, and D. Quillen. (2016)cite arxiv:1603.02199Comment: This is an extended version of "Learning Hand-Eye Coordination for Robotic Grasping with Large-Scale Data Collection," ISER 2016. Draft modified to correct typo in Algorithm 1 and add a link to the publicly available dataset.
L. Rozo, S. Calinon, and D. Caldwell. Robot and Human Interactive Communication, 2014 RO-MAN: The 23rd IEEE International Symposium on, page 619--624. IEEE, (2014)
J. Parker, A. Khoogar, and D. Goldberg. Robotics and Automation, 1989. Proceedings., 1989 IEEE International Conference on, page 271--276. IEEE, (1989)
S. Kawaji, T. Maeda, and N. Matsunaga. IFAC Proceedings Volumes, 26 (2, Part 3):
535 - 540(1993)12th Triennal Wold Congress of the International Federation of Automatic control. Volume 3 Applications I, Sydney, Australia, 18-23 July.
A. Zeng, S. Song, S. Welker, J. Lee, A. Rodriguez, and T. Funkhouser. (2018)cite arxiv:1803.09956Comment: Under review at the International Conference On Intelligent Robots and Systems (IROS) 2018. Project webpage: http://vpg.cs.princeton.edu.
K. Anjyo, H. Ochiai, and B. Barsky. Synthesis Lectures on Visual Computing: Computer Graphics, Animation, Computational Photography and Imaging Morgan & Claypool Publishers, (2017)
A. Chaabani, M. Bellamine, and M. Gasmi. International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), 3 (4):
17(November 2014)