activity
20192026
most citedImplicit 3D Orientation Learning for 6D Object Detection from RGB Images

5 citations · 5 across the 7 of their papers we have counts for

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cs.RO2026

Trinity: Unifying Class-Agnostic Terrain and Semantic Segmentation for Unstructured Outdoor Environments by Leveraging Synthetic Data

Marcus G Müller, Wout Boerdijk, Maximilian Durner +5

Terrain understanding is fundamental for mobile robots operating in unstructured outdoor environments. Existing vision-based traversability estimation methods rely on robot-specifi…

cs.RO2026

Markerless Robot Detection and 6D Pose Estimation for Multi-Agent SLAM

Markus Rueggeberg, Maximilian Ulmer, Maximilian Durner +4

The capability of multi-robot SLAM approaches to merge localization history and maps from different observers is often challenged by the difficulty in establishing data association…

cs.RO2024

Unknown Object Grasping for Assistive Robotics

Elle Miller, Maximilian Durner, Matthias Humt +5

We propose a novel pipeline for unknown object grasping in shared robotic autonomy scenarios. State-of-the-art methods for fully autonomous scenarios are typically learning-based a…

cs.RO2023

Density-based Feasibility Learning with Normalizing Flows for Introspective Robotic Assembly

Jianxiang Feng, Matan Atad, Ismael Rodríguez +3

Machine Learning (ML) models in Robotic Assembly Sequence Planning (RASP) need to be introspective on the predicted solutions, i.e. whether they are feasible or not, to circumvent…

cs.RO2021

Introspective Robot Perception using Smoothed Predictions from Bayesian Neural Networks

Jianxiang Feng, Maximilian Durner, Zoltan-Csaba Marton +2

This work focuses on improving uncertainty estimation in the field of object classification from RGB images and demonstrates its benefits in two robotic applications. We employ a (…