Jan Peters
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jan-peters.bsky.social
Jan Peters
@jan-peters.bsky.social
#RobotLearning Professor (#MachineLearning #Robotics) at @ias-tudarmstadt.bsky.social of
@tuda.bsky.social @dfki.bsky.social @hessianai.bsky.social
Reposted by Jan Peters
@timschneider94.bsky.social will present "Analysing the Interplay of Vision and Touch for Dexterous Insertion Tasks" by Janis Lenz, Tim Schneider, Theo Gruner, @daniel-palenicek.bsky.social, and
@jan-peters.bsky.social

🗓️ 13.06, 16:30 - 19:30
📍 Poster 100
See bsky.app/profile/tims...
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

🧵
June 13, 2025 at 11:06 AM
Reposted by Jan Peters
Our work introduces a geometrically-aware approach that brings motion planning into Bayesian goal inference—an early but promising direction.

With @anindex.bsky.social , Theo Gruner, @joemwatson.bsky.social , @georgiachal.bsky.social & @jan-peters.bsky.social
Bluesky
l.bsky.social
June 13, 2025 at 11:18 AM
Reposted by Jan Peters
@kay-pompetzki.bsky.social will present "Geometrically-Aware Goal Inference: Leveraging Motion Planning as Inference" by Kay Pompetzki, @anindex.bsky.social, Theo Gruner, @georgiachal.bsky.social, and @jan-peters.bsky.social

🗓️ 13.06, 16:30 - 19:30
📍 Poster 86
See bsky.app/profile/kay-...
June 13, 2025 at 11:21 AM
Reposted by Jan Peters
🦾 By combining EPVFs with massive parallelism and careful regularization, we close the gap with state-of-the-art DRL in complex environments.
🔗 Full paper: arxiv.org/abs/2502.11949
✨ Finally, many thanks to @jan-peters.bsky.social and
@ias-tudarmstadt.bsky.social for the support!
Massively Scaling Explicit Policy-conditioned Value Functions
We introduce a scaling strategy for Explicit Policy-Conditioned Value Functions (EPVFs) that significantly improves performance on challenging continuous-control tasks. EPVFs learn a value function V(...
arxiv.org
June 13, 2025 at 11:50 AM
Reposted by Jan Peters
We will also present "Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization" by @daniel-palenicek.bsky.social, Florian Vogt, @joemwatson.bsky.social, and @jan-peters.bsky.social.

🗓️ 13.06, 16:30 - 19:30
📍 Poster 50
See bsky.app/profile/did:...
June 13, 2025 at 2:01 PM
Reposted by Jan Peters
Or come to my talk @ International Symposium on Adaptive Motion of Animals and Machines and LokoAssist Symposium (AMAM) on Friday at TU Darmstadt

Thanks to @ias-tudarmstadt.bsky.social, @jan-peters.bsky.social
July 2, 2025 at 6:19 PM
Reposted by Jan Peters
Today, @theovincent.bsky.social l will present "Eau De Q-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning" by Théo Vincent, @jan-peters.bsky.social, and Carlo D'Eramo.
🗓️ 12.06, 16:30 - 19:30
📍 Poster 28
See bsky.app/profile/theo...
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
June 12, 2025 at 2:56 PM
Reposted by Jan Peters
@timschneider94.bsky.social will present "Active Perception for Tactile Sensing: A Task-Agnostic Attention-Based Approach" by Tim Schneider, Cristiana de Farias, Roberto Calandra, Liming Chen, and @jan-peters.bsky.social
🗓️ 12.06, 16:30 - 19:30
📍 Poster 105
See bsky.app/profile/tims...
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
June 12, 2025 at 2:57 PM
Reposted by Jan Peters
April 18, 2025 at 10:47 PM
Reposted by Jan Peters
Many thanks to my colleagues and collaborators: Daniel Palenicek, Łukasz Antczak, @jan-peters.bsky.social and most importantly Jonathan Kinzel (@ibims1jfk.bsky.social), who interned at MAB Robotics and did the experiments.
Also thanks to MAB Robotics for providing the hardware and constant support!
March 18, 2025 at 10:24 PM
Reposted by Jan Peters
We build on the efficient CrossQ DRL algorithm and combine it with two control architectures — Joint Target Prediction for agile maneuvers and Central Pattern Generators for stable, natural gaits — to train locomotion policies directly on the HoneyBadger quadruped robot from MAB Robotics.
March 18, 2025 at 10:24 PM
Reposted by Jan Peters
Intrigued? Check out the paper and videos here: nico-bohlinger.github.io/gait_in_eigh...
Gait in Eight
nico-bohlinger.github.io
March 18, 2025 at 10:24 PM
Thanks!
March 4, 2025 at 10:21 AM
Thanks!
March 4, 2025 at 10:21 AM