Dieter’s IROS Plenary on Unifying Model-based and Learning-based Robotics is now posted on youtube.
Author Archives: Dieter Fox
Tanner wins Best Robotic Vision Paper Award at ICRA 2017
Tanner’s paper on Self-Supervised Descriptor Learning won the ICRA 2017 Best Vision Paper Award.
Congratulations Tanner!
Arun’s and Tanner’s papers are finalists for ICRA Best Vision Paper Awrd
Arun’s paper on SE3-Nets and Tanner’s paper on Self-Supervised Descriptor Learning are finalists for the ICRA 2017 Best Vision Paper Awards.
Congratulations, and keep your fingers crossed!
2017 AAAI Classic Paper Award goes to Monte Carlo Localization paper
Dieter’s paper Monte Carlo Localization: Efficient Position Estimation for Mobile Robots, co-authored with Frank Dellaert, Wolfram Burgard, and Sebastian Thrun at AAAI 1999, just received the 2017 AAAI Classic Paper Award.
See here for the UW CSE blog post.
Welcome Sidd!
Sidd Srinivasa will join the robotics faculty at UW this fall! We’re all extremely excited to have him as a collaborator. Click here for more details.
Yuyin finished her PhD
Congratulations to Yuyin Sun on her successful PhD defense. Take a look at her thesis Toward Never-Ending Object Learning for Robots, it’s great!
Dieter’s ICRA-16 Keynote posted
Dieter’s ICRA Keynote is now on youtube.
Maya Cakmak receives NSF Career Award!
Congratulations to our colleague Maya Cakmak for receiving an NSF Career Award for her project on End-User Programming of General-Purpose Robots. Way to go, Maya!
2016 AAAI Classic Paper Award goes to Museum Tourguide Paper
The paper entitled The Interactive Museum Tour-Guide Robot, published at AAAI 1998, just received the 2016 AAAI Classic Paper Award.
See here for a nice UW CSE blog post.
Welcome new UW robotics faculty!
Welcome to Sawyer Fuller and Sam Burden, who just arrived at UW. Sawyer joined the ME Department and does very cool work on insect-scale robots, and Sam is now with the EE Department working on sensorimotor and neuromechanical control. In Spring, Sergey Levine will join CSE in Spring 2016, continuing his work on deep learning for robot control and perception.