230 citations · 528 across the 11 of their papers we have counts for
13 papers
Declarative Reactive Robot Behaviors from Imperative Language Models
Vincent Berenz, Tasha Kim, Bernhard Schölkopf
Large Language Models (LLMs) are predominantly trained on imperative programming languages, and existing work on LLM-based robot programming reflects this: it focuses on goal-direc…
Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion
Simon Guist, Jan Schneider, Hao Ma +9
Operating robots precisely and at high speeds has been a long-standing goal of robotics research. Balancing these competing demands is key to enabling the seamless collaboration of…
Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80
Vincent Berenz, Felix Widmaier, Simon Guist +2
Robotic applications require the integration of various modalities, encompassing perception, control of real robots and possibly the control of simulated environments. While the st…
Hindsight States: Blending Sim and Real Task Elements for Efficient Reinforcement Learning
Simon Guist, Jan Schneider, Alexander Dittrich +3
Reinforcement learning has shown great potential in solving complex tasks when large amounts of data can be generated with little effort. In robotics, one approach to generate trai…
normflows: A PyTorch Package for Normalizing Flows
Vincent Stimper, David Liu, Andrew Campbell +4
Normalizing flows model probability distributions through an expressive tractable density. They transform a simple base distribution, such as a Gaussian, through a sequence of inve…
Real Robot Challenge: A Robotics Competition in the Cloud
Stefan Bauer, Felix Widmaier, Manuel Wüthrich +39
Dexterous manipulation remains an open problem in robotics. To coordinate efforts of the research community towards tackling this problem, we propose a shared benchmark. We designe…
Learning Event-triggered Control from Data through Joint Optimization
Niklas Funk, Dominik Baumann, Vincent Berenz +1
We present a framework for model-free learning of event-triggered control strategies. Event-triggered methods aim to achieve high control performance while only closing the feedbac…
TriFinger: An Open-Source Robot for Learning Dexterity
Manuel Wüthrich, Felix Widmaier, Felix Grimminger +12
Dexterous object manipulation remains an open problem in robotics, despite the rapid progress in machine learning during the past decade. We argue that a hindrance is the high cost…
Learning to Play Table Tennis From Scratch using Muscular Robots
Dieter Büchler, Simon Guist, Roberto Calandra +3
Dynamic tasks like table tennis are relatively easy to learn for humans but pose significant challenges to robots. Such tasks require accurate control of fast movements and precise…
Safe and Fast Tracking on a Robot Manipulator: Robust MPC and Neural Network Control
Julian Nubert, Johannes Köhler, Vincent Berenz +2
Fast feedback control and safety guarantees are essential in modern robotics. We present an approach that achieves both by combining novel robust model predictive control (MPC) wit…
An Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research
Felix Grimminger, Avadesh Meduri, Majid Khadiv +10
We present a new open-source torque-controlled legged robot system, with a low-cost and low-complexity actuator module at its core. It consists of a high-torque brushless DC motor…
Learning Sensory-Motor Associations from Demonstration
Vincent Berenz, Ahmed Bjelic, Lahiru Herath +1
We propose a method which generates reactive robot behavior learned from human demonstration. In order to do so, we use the Playful programming language which is based on the react…
Real-time Perception meets Reactive Motion Generation
Daniel Kappler, Franziska Meier, Jan Issac +7
We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models and hard-to-pred…