Robotics Today   -   A Series of Technical Talks
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"Robotics Today - A series of technical talks" is a virtual robotics seminar series. The goal of the series is to bring the robotics community together during these challenging times. The seminars are scheduled on Fridays at 3PM EST (12AM PST) and are open to the public. The format of the seminar consists of a technical talk live captioned and streamed via Web and Twitter (@RoboticsSeminar), followed by an interactive discussion between the speaker and a panel of faculty, postdocs, and students that will moderate audience questions.

Stay up to date with upcoming seminars with the Robotics Today Google Calendar (or download the .ics file) and view past seminars on the Robotics Today Youtube Channel. And follow us on Twitter!

Upcoming Seminars

Seminars will be broadcast at 3PM EST (12PM PST) here.

Upcoming IFRR Colloquia

The International Foundation of Robotics Research (IFRR) is hosting a bi-weekly colloquia to "provide a platform for open discussion and interaction on diverse themes in robotics". For more information the colloquia and to see the past colloquia, please visit here. Below is the information on the upcoming colloquia!

Probabilistic Robotics and Autonomous Driving

Date and time: March 4 at 2:00pm PST/ 5:00pm EST/ 11:00pm CET
Live Stream: Zoom Webinar
Live questions and discussion: Slido
Moderator: Henrik I. Christensen
Speaker: Wolfram Burgard

Abstract: For autonomous robots and automated driving, the capability to robustly perceive their environments and execute their actions is the ultimate goal. The key challenge is that no sensors and actuators are perfect, which means that robots and cars need the ability to properly deal with the resulting uncertainty. In this presentation, I will introduce the probabilistic approach to robotics, which provides a rigorous statistical methodology to solve the state estimation problem. I will furthermore discuss how this approach can be extended using state-of-the-art technology from machine learning to bring us closer to the development of truly robust systems able to serve us in our every-day lives. In this context, I will in particular focus on the data advantage that the Toyota Research Institute is planning to leverage in combination with self-/semi-supervised methods for machine learning to speed up the process of developing self-driving cars.

Past Seminars

Videos of the recorded seminars will be posted about a week after the talk.