Publications

2025

FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Action Flow Policies

Moritz Reuss, Hongyi Zhou, Marcel Rühle, Ömer Erdinç Yağmurlu, Fabian Otto, Rudolf Lioutikov
ICLR Robot Learning Workshop - Towards Robots with Human-Level Abilities

Efficient Off-Policy Learning for High-Dimensional Action Spaces

Fabian Otto, Philipp Becker, Vien Anh Ngo, Gerhard Neumann
International Conference for Learning Representations (ICLR)

2024

Combining Reconstruction and Contrastive Methods for Multimodal Representations in RL

Philipp Becker, Sebastian Mossburger, Fabian Otto, Gerhard Neumann
Reinforcement Learning Conference (RLC)

Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning

Ge Li, Hongyi Zhou, Dominik Roth, Serges Thilges, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann
International Conference for Learning Representations (ICLR)

2023

MP3: Movement Primitive-Based (Re-)Planning Policy

Fabian Otto, Hongyi Zhou, Onur Celik, Ge Li, Rudolf Lioutikov, Gerhard Neumann
CoRL Workshop on Learning Effective Abstractions for Planning (LEAP)

ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives

Ge Li, Zeqi Jin, Michael Volpp, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann
IEEE Robotics and Automation Letters (RA-L)
International Conference on Intelligent Robots and Systems (IROS)

2022

Deep Black-Box Reinforcement Learning with Movement Primitives

Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann
Conference on Robot Learning (CoRL)

2021

Differentiable Trust Region Layers for Deep Reinforcement Learning

Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Ziesche, Gerhard Neumann
International Conference for Learning Representations (ICLR)

2020

Model-free Deep Reinforcement Learning – Algorithms and Applications

Fabian Otto
Reinforcement Learning Algorithms: Analysis and Applications. Studies in Computational Intelligence, vol 883.