We got 6 papers accepted at the European Workshop on #ReinforcementLearning (#EWRL)! Congrats to my amazing students and colleagues! See you in #Toulouse! A thread on our papers 🧵

Humbled to be included in this list curated by Ben Eysenbach! Please consider inviting more women+ to your planned events. Recognize, retain, and attract more diverse talent!

The LiteRL group is seeking 1 #postdoc in #reinforcementlearning and #robotlearning. We gladly welcome applications from whoever has a strong passion for #RL and wants to keep conducting cutting-edge research after the Ph.D.. More details at drive.google.com/file/d/147FrkO…

I am excited to share that our work "Evetac: An Event-based Optical Tactile Sensor for Robotic Manipulation" got accepted for publication in the IEEE Transactions on Robotics (T-RO). Intelligent Autonomous Systems Group LASR Lab Tactile Internet SECAI: School of Embedded Composite AI Roberto Calandra Georgia Chalvatzaki Jan Peters

Check out our new Survey in Deep Generative Models for Robotics! We discuss different aspects of the application of DGMs and investigate how to improve generalisation in Behavioral Cloning.

The Women In Engineering (WIE) lunch organized by RAS was a real success! Congratulations to all the women who have been awarded 👏🏻👩‍🎓🤖 #ieee #ieeeras #CASE2024 #WIE

What a great success for Georgia Chalvatzaki Justus Thies Alexander Tichai, Pelin Tozmann and the #TUDa: Four young researchers from TU Darmstadt have been awarded a Starting Grant by the European Research Council European Research Council (ERC) tu-darmstadt.de/universitaet/a…

Check out some information about our ERC Starting Grant SIREN at pearl-lab.com/erc-starting-g… #FrontierResearch #ERCStG #Robots #ArtificialIntelligence #RobotLearning Horizon Europe🇪🇺 European Research Council (ERC) TU Darmstadt Computer Science, TU Darmstadt hessian.AI

Do you need a quick way to compute collision probabilities to ensure the safety of your mobile robot planning algorithm? Take a look at our latest RA-L paper: "Safe and Efficient Path Planning under Uncertainty via Deep Collision Probability Fields" ieeexplore.ieee.org/document/10670…

It is a great honour to serve as Workshops Chair for Conference on Robot Learning but it was such a difficult task to decide among high quality submissions. Apart from a reviewing process, we also considered the diversity of topics and speakers. We hope you enjoy our selected events!

aaand it’s a wrap! M2L school ended with a dive into code generation with Kate Baumli, graph neural networks with Helena Andres Terre and deep robotics with Georgia Chalvatzaki! Over 22+h of lectures, lots of conversations and connections, it will take some weeks to digest everything 🤧

It was great participating at the M2L school in Milano. I gave a brief tutorial on Robot Learning covering hot topics on imitation learning with generative models & robotic reinforcement learning. Thanks to organisers for inviting me & to participants for the great questions

arxiv.org/abs/2409.04306 Safe and efficient path planning under uncertainty via deep collision probability fields. Title and figure 1 tells everything.