I'm super excited to have been named an #NVIDIA Graduate Fellowship Finalist! 💚 Huge thanks to my supervisor @jan-peters.bsky.social and all my collaborators. Can't wait to join the NVIDIA Seattle Robotics Lab for my internship next summer! 🤖 blogs.nvidia.com/blog/graduat...

Had a really great time presenting our #NeurIPS paper at the poster session today. Thanks to everyone who stopped by. If you are interested in sample-efficient #RL, check out our work: Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization

I'm presenting four different works at IROS 2025 this week in Hangzhou 🤖

Warming up for #IROS2025 🔥 We’re releasing CaDeLaC as open source! - Training pipeline - Integration with acados for adaptive physics-consistent MPC - Simulation + real Franka torque control 💻 github.com/Schulze18/ca... @ias-tudarmstadt.bsky.social @jan-peters.bsky.social @olegarenz.bsky.social

🚀 New preprint! Introducing XQC— a simple, well-conditioned actor-critic that achieves SOTA sample efficiency in #RL ✅ ~4.5× fewer parameters than SimbaV2 ✅ Scales to vision-based RL 👉 arxiv.org/pdf/2509.25174 Thanks to Florian Vogt @joemwatson.bsky.social @jan-peters.bsky.social

🇰🇷 Conferences are about finally meeting your collaborators from all around the world! Check out our work on Embodiment Scaling Laws @CoRL2025 We investigate cross-embodiment learning as the next axis of scaling for truly generalist policies 📈 🔗 All details: embodiment-scaling-laws.github.io

As usual, @ewrl18.bsky.social was a wonderful experience. I had the pleasure of presenting my research as a Contributed Talk 🎉 Special thanks to the organizers for making it happen!

Pushing for #icra but still missing real robot experiments? 😰 Skip the ROS headaches — get your Franka robot running in minutes with franky! 🦾 Super beginner-friendly, Pythonic, and fast to set up. 🔗 github.com/TimSchneider... @ias-tudarmstadt.bsky.social @jan-peters.bsky.social

🎉Our paper "Context-Aware Deep Lagrangian Networks for MPC" was accepted at #IROS2025! We present CaDeLaC: adaptive physics-consistent robot control via online SysID + MPC. Paper: arxiv.org/abs/2506.15249 Big thanks to @ias-tudarmstadt.bsky.social @jan-peters.bsky.social @olegarenz.bsky.social

Had an amazing time presenting my research @cohereforai.bsky.social yesterday 🎤 In case you could not attend, feel free to check it out 👉 youtu.be/RCA22JWiiY8?...

Robot Randomization is fun!

🚀 Checkout our new work at @rldmdublin2025.bsky.social today at poster#16! We're showing how to make Explicit Policy-conditioned Value Functions V(θ) (originating from Faccio & Schmidhuber) work for more complex control tasks. The secret? Massive scaling!

Stoked to present another work at RLDM 2025! If you’re into dexterous robotics, multimodal RL, or tactile sensing, swing by Poster 100 today to see what we cooked up 🦾✨ #Robotics #TactileSensing #RL #DexterousManipulation @ias_tudarmstadt 🧵

IAS is at RLDM 2025! We have many exiting works to share (see 👇), so come to our posters and talk to us!

Excited to present our latest work at RLDM 2025! If you’re curious about tactile sensing, active perception, or RL in robotics, stop by my poster. Here’s what we’ve been up to: 🧵 #Robotics #TactileSensing #ReinforcementLearning #Transformers #ActivePerception @ias-tudarmstadt.bsky.social

Very excited to present 🎉Eau De Q-Network🎉 on Thursday @rldmdublin2025.bsky.social Poster #28 🔍Eau De Q-Network gradually prunes the network weights at the agent's learning pace, ultimately reaching a final sparsity level that is discovered by the algorithm!🔎 👉📰 arxiv.org/pdf/2503.01437

🚀 New preprint "Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization"🤖 We propose CrossQ+WN, a simple yet powerful off-policy RL for more sample-efficiency and scalability to higher update-to-data ratios. 🧵 t.co/Z6QrMxZaPY #RL @ias-tudarmstadt.bsky.social

Check out LocoMuJoCo2!

⚡️ Do you think training robot locomotion needs large scale simulation? Think again! We train an omnidirectional locomotion policy directly on a real quadruped in just a few minutes 🚀 Top speeds of 0.85 m/s, two different control approaches, indoor and outdoor experiments, and more! 🤖🏃‍♂️

That unboxing hit differently—a 300 kg crate! We just set up our Talos robot and can't wait to share some exciting demos soon. Stay tuned! 🤖

🎉 Meet TALOS2, our humanoid robot nicknamed “HAINER”! 🤖📦 Congrats to those who guessed right! With full torque control, ROS integration, and designed for locomotion and manipulation, this bipedal robot will advance robotics research. Watch its first steps—more to come! 🚀

Something exciting just arrived at our lab! Here's a hint: precision mechanics, intricate wiring, and a touch of power. What could it be? A) High-end lab equipment B) Experimental space probe component C) Something that might walk past you in the hallway. Share your guesses!

Congratulations once again, Dr. Watson! Ph.D. graduate #40! Your dedication and hard work have truly paid off, and that PhD hat is a testament to all your efforts. Hope to see the adventures awaiting with your future dog Sherlock Holmes! Here's to many more achievements and exciting journeys ahead.

Puze Liu's PhD work brings safe exploration and policy learning to robot reinforcement learning. He develops algorithms that ensure safety without compromising performance, crucial for real world robotics.

If you're interested in cutting-edge research on diffusion models in robot manipulation, you should definitely explore Joao Carvalho's remarkable work at @ias_tudarmstadt. A significant milestone was just achieved as he successfully defended his PhD thesis, marking our first defense of 2025.

Great work by great students, alumni Julen Urain, Carlo D'Eramo, Boris Belousov & Jens Kober and with our great collaborators Constantin A. Rothkopf! Happy with the 2025 results at International Conference on Learning Representations (ICLR).

Hello world! Follow for posts from the IAS group at TU Darmstadt, researching the intersection of #robotics and #machinelearning!