24 citations · 45 across the 18 of their papers we have counts for
18 papers
Multi-Resolution Tactile Imitation Learning for Contact-Rich Robotic Manipulation
Rickmer Krohn, Erik Helmut, Niklas Funk +3
Touch sensing is beneficial for solving a wide variety of manipulation tasks. While there exists a wide range of tactile sensors with different properties, exploiting the fusion of…
Neuromorphic BrailleNet: Accurate and Generalizable Braille Reading Beyond Single Characters through Event-Based Optical Tactile Sensing
Naqash Afzal, Niklas Funk, Erik Helmut +2
Conventional robotic Braille readers typically rely on discrete, character-by-character scanning, limiting reading speed and disrupting natural flow. Vision-based alternatives ofte…
SE(3)-PoseFlow: Estimating 6D Pose Distributions for Uncertainty-Aware Robotic Manipulation
Yufeng Jin, Niklas Funk, Vignesh Prasad +4
Object pose estimation is a fundamental problem in robotics and computer vision, yet it remains challenging due to partial observability, occlusions, and object symmetries, which i…
Tactile-Conditioned Diffusion Policy for Force-Aware Robotic Manipulation
Erik Helmut, Niklas Funk, Tim Schneider +2
Contact-rich manipulation depends on applying the correct grasp forces throughout the manipulation task, especially when handling fragile or deformable objects. Most existing imita…
On the Importance of Tactile Sensing for Imitation Learning: A Case Study on Robotic Match Lighting
Niklas Funk, Changqi Chen, Tim Schneider +3
The field of robotic manipulation has advanced significantly in recent years. At the sensing level, several novel tactile sensors have been developed, capable of providing accurate…
Particle-based 6D Object Pose Estimation from Point Clouds using Diffusion Models
Christian Möller, Niklas Funk, Jan Peters
Object pose estimation from a single view remains a challenging problem. In particular, partial observability, occlusions, and object symmetries eventually result in pose ambiguity…
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics
Puze Liu, Jonas Günster, Niklas Funk +17
Machine learning methods have a groundbreaking impact in many application domains, but their application on real robotic platforms is still limited. Despite the many challenges ass…
Learning Force Distribution Estimation for the GelSight Mini Optical Tactile Sensor Based on Finite Element Analysis
Erik Helmut, Luca Dziarski, Niklas Funk +2
Contact-rich manipulation remains a major challenge in robotics. Optical tactile sensors like GelSight Mini offer a low-cost solution for contact sensing by capturing soft-body def…
ActionFlow: Equivariant, Accurate, and Efficient Policies with Spatially Symmetric Flow Matching
Niklas Funk, Julen Urain, Joao Carvalho +3
Spatial understanding is a critical aspect of most robotic tasks, particularly when generalization is important. Despite the impressive results of deep generative models in complex…
Evetac: An Event-based Optical Tactile Sensor for Robotic Manipulation
Niklas Funk, Erik Helmut, Georgia Chalvatzaki +2
Optical tactile sensors have recently become popular. They provide high spatial resolution, but struggle to offer fine temporal resolutions. To overcome this shortcoming, we study…
Placing by Touching: An empirical study on the importance of tactile sensing for precise object placing
Luca Lach, Niklas Funk, Robert Haschke +4
This work deals with a practical everyday problem: stable object placement on flat surfaces starting from unknown initial poses. Common object-placing approaches require either com…
SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion
Julen Urain, Niklas Funk, Jan Peters +1
Multi-objective optimization problems are ubiquitous in robotics, e.g., the optimization of a robot manipulation task requires a joint consideration of grasp pose configurations, c…
Graph-based Reinforcement Learning meets Mixed Integer Programs: An application to 3D robot assembly discovery
Niklas Funk, Svenja Menzenbach, Georgia Chalvatzaki +1
Robot assembly discovery is a challenging problem that lives at the intersection of resource allocation and motion planning. The goal is to combine a predefined set of objects to f…
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…
Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation
Niklas Funk, Charles Schaff, Rishabh Madan +10
Dexterous manipulation is a challenging and important problem in robotics. While data-driven methods are a promising approach, current benchmarks require simulation or extensive en…
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…
Developing a Purely Visual Based Obstacle Detection using Inverse Perspective Mapping
Julian Nubert, Niklas Funk, Fabio Meier +1
Our solution is implemented in and for the frame of Duckietown. The goal of Duckietown is to provide a relatively simple platform to explore, tackle and solve many problems linked…
Autonomous Electric Race Car Design
Niklas Funk, Nikhilesh Alatur, Robin Deuber +12
Autonomous driving and electric vehicles are nowadays very active research and development areas. In this paper we present the conversion of a standard Kyburz eRod into an autonomo…