🚨Super excited to be presenting our latest work on pose estimation in space 🚀 at #IROS2023 @ieeeiros: “6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics” @DLR_de Paper: https://t.co/akmgqBPRGN Code: https://t.co/18uz9X5E4C (stay tuned)

Congratulations to *Dr.* @mwoerhe for exceptional work over the past years, an excellent thesis, and an outstanding defense talk!! I was really lucky and am more than grateful to have had you as the first PhD student in my team 🎉🎉🎉

Felt pretty special to have so many coauthors at the poster session @ieeeiros @MaxlDur @StoiberMa! With only @ma_sundermeyer missing! #IROS2023

We achieve state-of-the-art on a satellite pose estimation challenge by @esaACT. Big shoutout to my amazing colleagues who made this work possible @MaxlDur @ma_sundermeyer @StoiberMa and Rudolph Triebel! Come to our #IROS2023 poster on Wednesday!

Idk about the Tesla robot video, something seems off

After several months of beta, we are happy to announce the release of Stable-Baselines3 (SB3) v1.0, a set of reliable implementations of reinforcement learning (RL) algorithms in PyTorch =D! Blog post: https://t.co/IvOqj0twCt GitHub: https://t.co/SlsjdrL1um

Really happy to see our review (and the first paper of my PhD 🥳) 'Multi-omics integration in biomedical research – A #metabolomics-centric review' out! Thank you to my amazing co-authors @JanKrumsiek, @KastenmullerLab,@_MatthiasArnold. https://t.co/vPjBHAikTa

Pretty excited about this collaboration. Obstacle avoidance for robotic manipulators is a hard problem, especially on the basis of vision. Our approach allows a seamless integration of a learned policy while maintaining the responsiveness required for many critical tasks.

If you ever wondered what makes different implementations of the same RL algorithm perform very differently on the same task, check out our latest #NeurIPS2020 deep RL workshop paper. Paper: https://t.co/48GJ1OSw1a Project: https://t.co/zhxkSxEuzB Code:

Really excited about this! For more information check out our session at #AAIC20 on "Genome-Metabolome-Phenome: Towards an Integrated Molecular Atlas for Alzheimer's Disease"

4/ special thanks to @kuoyi_chao for cutting the video!

3/ Their implementation has never seen the configuration of the challenge before and had to adapt to different poses and deteriorating effects, such as occlusion. They overcame the challenge via a robust computer vision pipeline and clever 3-d printed gripper design.

2/ Big thank you to all the participants and our staff for helping us.

1/ Wrapped-up our #CoastalCleanUp Robothon! @kuoyi_chao, @johannesack and their team took it home and will compete in the @automaticafair Robothon! Have a look at their impressive run in the finals https://t.co/x4as2bTd9y #Hackathon #Robotics

We just won the Robothon at @MSRM_TUM ! 🎉 Special thanks to our supervisors for supporting us. We had a really challenging week and we are looking forward to the next challenge. #Robothon #Hackathon #Robotics #TUM

The last 24 hours are on!

We finally received the confirmation that the winners of our student @MSRM_TUM #Robothon will get free entry to compete at @automaticafair in June (for a price pool of 50k €)!

Really interesting competition organized by @maxwulmer! Looking forward to hearing about innovations in robotics-aided climate protection!

Each year, about 7 million tons of plastics end up in the ocean of which a substantial amount is washed ashore. The challenge this year is to build a robust solution that can autonomously separate waste from gravel and sand to accelerate the cleaning process of coastal areas.

Kicking-off this year's Robothon at the @MSRM_TUM! Teams of students compete to come up with innovative ideas for the challenge "#CoastalCleanUp: Robotics-aided Climate Protection". #Hackathon #Robotics