Frederik Ebert

🚀 I’m excited to share a big milestone for Emancro! We’ve successfully piloted our AI-powered robot at one of the leading US hospitals taking on one of the most critical and error-prone hospital logistics tasks: medication cabinet restocking. At the core is GEDIA — our proprietary Generalizable Dexterous Intelligent Agent that gives our robots the ability to adapt and perform complex tasks at scale. 👉 Watch the robot in action: (youtube.com/watch?v=QZbx89…) 👉 Learn more about Emancro: (emancro.ai) And this is only the beginning 🤖. We’re already developing our next-gen robot to expand into medical supply distribution, lab sample logistics, food, and linen services — on track to automate the majority of logistics tasks in hospitals and beyond.

We've updated Bridge Data with 33k robot demos, 8.8k autonomous rollouts, 21 environments, and a huge number of tasks! Check out the new Bridge Data website: rail-berkeley.github.io/bridgedata/ The largest and most diverse public dataset of robot demos is getting bigger and bigger!

Please find more information here: sites.google.com/berkeley.edu/n…

@Tianyi_Zh @ancadianadragan We will post a link to the YouTube live-stream on the event-website I just tweeted. If you want to be a student speaker please email me: febert@berkeley.edu. You can also share your thoughts with everyone by filling out the questions in the GoogleForm linked on the website.

@febert8888 @ancadianadragan how to participate? Will there be a zoom link? I have registered through the Google form in the link.

We developed a touch-sensing robotic "thumb," extending on the GelSight design, that can sense contacts on multiple sides, and use deep nets to learn how to insert a plug into an outlet. w/ A. Padmanabha, F. Ebert, S. Tian, @RCalandra, @chelseabfinn sites.google.com/berkeley.edu/o…

Learning to grasp & insert a plug with only tactile feedback, using a bright new sensor based on the GelSight design. arxiv.org/abs/2003.06965 w/ Akhil Padmanabha, @febert8888, Stephen Tian, @RCalandra, @svlevine

RoboNet: a new large-scale dataset collected across multiple robots, labs, viewpoints, and objects, for studying generalization of predictive models and controllers across different robots! arxiv.org/abs/1910.11215 robonet.wiki video: youtube.com/watch?v=qd-sBi…

Tired of your robot learning from scratch? We introduce RoboNet: a dataset that enables fine-tuning to new views, new envs, & entirely new robot platforms. robonet.wiki arxiv.org/abs/1910.11215 w/ Dasari @febert8888 Tian @SurajNair_1 Bucher Schmeckpeper Singh @svlevine

Check out our work on "Manipulation by Feel: Touch-Based Control with Deep Predictive Models". bair.berkeley.edu/blog/2019/03/2…

@neuroecology Thloonlpp Llol

I love collecting animal videos that show off that they have feelings and emotions and weird cognitive abilities, here are a few I've found in the past few months Here's a frustrated and exasperated raccoon MERRY CHRISTMAS

Check out our work on video-prediction based robotic manipulation: