4 citations · 4 across the 12 of their papers we have counts for
14 papers
CrossBFM: Distilling a Shared Latent Behavior Space Across Humanoid Embodiments
Tan-Dzung Do, Tuan Dat Phuong, Nico Bohlinger +6
Behavior Foundation Models (BFMs) give humanoids a promptable policy over a latent behavior space, enabling one single vector to represent a motion to imitate, a pose to reach, or…
ChronoSRL: Temporal Geometry for Self-Supervised Reinforcement Learning
Nico Bohlinger, Jan Peters
A goal that is close in space can be far away in time. Obstacles, terrain, and the agent's own capabilities determine how long it takes to get there. Yet, critics in contrastive an…
Rapid Embodiment Adaptation for Quadrupedal Locomotion
Dichen Li, Bo Ai, Nico Bohlinger +3
Humans readily adapt their movements as their bodies change through aging, injury, or load carrying, but learning-based robot policies often break when hardware properties shift. W…
Shape Your Body: Value Gradients for Multi-Embodiment Robot Design
Nico Bohlinger, Jan Peters
We propose to turn generalist multi-embodiment value functions into reusable models for robot design. Instead of running a new reinforcement learning co-design loop for each robot,…
Active Embodiment Identification with Reinforcement Learning for Legged Robots
Nico Bohlinger, Jan Peters
We present an active embodiment identification method for legged robots that jointly learns information-seeking behavior and explicit embodiment prediction. Using a history-augment…
Evaluation of an Actuated Spine in Agile Quadruped Locomotion
Nico Bohlinger, Piotr Kicki, Davide Tateo +2
The spine plays a crucial role in the dynamic locomotion of quadrupedal animals, improving the stability, speed, and efficiency of their gait, especially for fast-paced and highly…
Bridge the Gap: Enhancing Quadruped Locomotion with Vertical Ground Perturbations
Maximilian Stasica, Arne Bick, Nico Bohlinger +5
Legged robots, particularly quadrupeds, excel at navigating rough terrains, yet their performance under vertical ground perturbations, such as those from oscillating surfaces, rema…
Multi-Embodiment Locomotion at Scale with extreme Embodiment Randomization
Nico Bohlinger, Jan Peters
We present a single, general locomotion policy trained on a diverse collection of 50 legged robots. By combining an improved embodiment-aware architecture (URMAv2) with a performan…
Robust Localization, Mapping, and Navigation for Quadruped Robots
Dyuman Aditya, Junning Huang, Nico Bohlinger +5
Quadruped robots are currently a widespread platform for robotics research, thanks to powerful Reinforcement Learning controllers and the availability of cheap and robust commercia…
Towards Embodiment Scaling Laws in Robot Locomotion
Bo Ai, Liu Dai, Nico Bohlinger +7
Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…
Gait in Eight: Efficient On-Robot Learning for Omnidirectional Quadruped Locomotion
Nico Bohlinger, Jonathan Kinzel, Daniel Palenicek +2
On-robot Reinforcement Learning is a promising approach to train embodiment-aware policies for legged robots. However, the computational constraints of real-time learning on robots…
Massively Scaling Explicit Policy-conditioned Value Functions
Nico Bohlinger, Jan Peters
We introduce a scaling strategy for Explicit Policy-Conditioned Value Functions (EPVFs) that significantly improves performance on challenging continuous-control tasks. EPVFs learn…
One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion
Nico Bohlinger, Grzegorz Czechmanowski, Maciej Krupka +4
Deep Reinforcement Learning techniques are achieving state-of-the-art results in robust legged locomotion. While there exists a wide variety of legged platforms such as quadruped,…
RL-X: A Deep Reinforcement Learning Library (not only) for RoboCup
Nico Bohlinger, Klaus Dorer
This paper presents the new Deep Reinforcement Learning (DRL) library RL-X and its application to the RoboCup Soccer Simulation 3D League and classic DRL benchmarks. RL-X provides…