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Niklas Funk

7 accepted papers

2025

Learning Force Distribution Estimation for the GelSight Mini Optical Tactile Sensor Based on Finite Element Analysis

IROS 2025

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 softbody deformations of the silicone gel. However, accurately inferring shear and normal force distributions from these gel deformat

Cited by 8SourcecodeScholar
2024

A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics

NeurIPS 2024poster

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 associated with combining machine learning technology with robotics, robot learning remains one of the most promising direc…

Cited by 0SourcePDFScholar
2023

Placing by Touching: An Empirical Study on the Importance of Tactile Sensing for Precise Object Placing

IROS 2023poster

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 complete scene specifications or extrinsic sensor measurements, e.g., cameras, that occasionally suffer from occlusions. We…

Cited by 11SourceScholar
2023

SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion

ICRA 2023poster

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, collisions and joint limits. While some demands can be easily hand-designed, e.g., the smoothness of a trajectory, severa…

Cited by 174SourcecodeScholar
2022

Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation

RA-L 2022

Dexterous manipulation is a challenging and important problem in robotics. While data-driven methods are a promising approach, current benchmarks require simulation or extensive engineering support due to the sample inefficiency of popular methods. We present benchmarks for the TriFinger system, an

Cited by 39SourcecodeScholar
2022

Graph-based Reinforcement Learning meets Mixed Integer Programs: An application to 3D robot assembly discovery

IROS 2022poster

Robot assembly discovery (RAD) 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 form something new while considering task execution with the robot-in-the-loop. In this work, we tackle the problem…

Cited by 16SourceScholar
2021

Learn2Assemble with Structured Representations and Search for Robotic Architectural Construction

CoRL 2021poster

Autonomous robotic assembly requires a well-orchestrated sequence of high-level actions and smooth manipulation executions. Learning to assemble complex 3D structures remains a challenging problem that requires drawing connections between target designs and building blocks, and creating valid assemb…

Cited by 56SourceScholar