71 citations · 228 across the 26 of their papers we have counts for
32 papers
Out-of-Distribution Detection for Adaptive Computer Vision
Simon Kristoffersson Lind, Rudolph Triebel, Luigi Nardi +1
It is well known that computer vision can be unreliable when faced with previously unseen imaging conditions. This paper proposes a method to adapt camera parameters according to a…
6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics
Maximilian Ulmer, Maximilian Durner, Martin Sundermeyer +2
We present a novel technique to estimate the 6D pose of objects from single images where the 3D geometry of the object is only given approximately and not as a precise 3D model. To…
Efficient and Feasible Robotic Assembly Sequence Planning via Graph Representation Learning
Matan Atad, Jianxiang Feng, Ismael Rodríguez +2
Automatic Robotic Assembly Sequence Planning (RASP) can significantly improve productivity and resilience in modern manufacturing along with the growing need for greater product cu…
Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking
Manuel Stoiber, Mariam Elsayed, Anne E. Reichert +3
In many applications of advanced robotic manipulation, six degrees of freedom (6DoF) object pose estimates are continuously required. In this work, we develop a multi-modality trac…
RECALL: Rehearsal-free Continual Learning for Object Classification
Markus Knauer, Maximilian Denninger, Rudolph Triebel
Convolutional neural networks show remarkable results in classification but struggle with learning new things on the fly. We present a novel rehearsal-free approach, where a deep n…
A Multi-body Tracking Framework - From Rigid Objects to Kinematic Structures
Manuel Stoiber, Martin Sundermeyer, Wout Boerdijk +1
Kinematic structures are very common in the real world. They range from simple articulated objects to complex mechanical systems. However, despite their relevance, most model-based…
Challenges of SLAM in extremely unstructured environments: the DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset
Riccardo Giubilato, Wolfgang Stürzl, Armin Wedler +1
We present the DLR Planetary Stereo, Solid-State LiDAR, Inertial (S3LI) dataset, recorded on Mt. Etna, Sicily, an environment analogous to the Moon and Mars, using a hand-held sens…
Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects
Manuel Stoiber, Martin Sundermeyer, Rudolph Triebel
Tracking objects in 3D space and predicting their 6DoF pose is an essential task in computer vision. State-of-the-art approaches often rely on object texture to tackle this problem…
A Model for Multi-View Residual Covariances based on Perspective Deformation
Alejandro Fontan, Laura Oliva, Javier Civera +1
In this work, we derive a model for the covariance of the visual residuals in multi-view SfM, odometry and SLAM setups. The core of our approach is the formulation of the residual…
SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World
Manuel Stoiber, Martin Pfanne, Klaus H. Strobl +2
Region-based methods have become increasingly popular for model-based, monocular 3D tracking of texture-less objects in cluttered scenes. However, while they achieve state-of-the-a…
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 (…
GPGM-SLAM: a Robust SLAM System for Unstructured Planetary Environments with Gaussian Process Gradient Maps
Riccardo Giubilato, Cedric Le Gentil, Mallikarjuna Vayugundla +3
Simultaneous Localization and Mapping (SLAM) techniques play a key role towards long-term autonomy of mobile robots due to the ability to correct localization errors and produce co…
Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions
Martin Wudenka, Marcus G. Müller, Nikolaus Demmel +4
In the future, extraterrestrial expeditions will not only be conducted by rovers but also by flying robots. The technical demonstration drone Ingenuity, that just landed on Mars, w…
Multi-Modal Loop Closing in Unstructured Planetary Environments with Visually Enriched Submaps
Riccardo Giubilato, Mallikarjuna Vayugundla, Wolfgang Stürzl +3
Future planetary missions will rely on rovers that can autonomously explore and navigate in unstructured environments. An essential element is the ability to recognize places that…
Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes
Martin Sundermeyer, Arsalan Mousavian, Rudolph Triebel +1
Grasping unseen objects in unconstrained, cluttered environments is an essential skill for autonomous robotic manipulation. Despite recent progress in full 6-DoF grasp learning, ex…
Unknown Object Segmentation from Stereo Images
Maximilian Durner, Wout Boerdijk, Martin Sundermeyer +3
Although instance-aware perception is a key prerequisite for many autonomous robotic applications, most of the methods only partially solve the problem by focusing solely on known…
Learning to Localize in New Environments from Synthetic Training Data
Dominik Winkelbauer, Maximilian Denninger, Rudolph Triebel
Most existing approaches for visual localization either need a detailed 3D model of the environment or, in the case of learning-based methods, must be retrained for each new scene.…
"What's This?" -- Learning to Segment Unknown Objects from Manipulation Sequences
Wout Boerdijk, Martin Sundermeyer, Maximilian Durner +1
We present a novel framework for self-supervised grasped object segmentation with a robotic manipulator. Our method successively learns an agnostic foreground segmentation followed…
Bayesian Optimization Meets Laplace Approximation for Robotic Introspection
Matthias Humt, Jongseok Lee, Rudolph Triebel
In robotics, deep learning (DL) methods are used more and more widely, but their general inability to provide reliable confidence estimates will ultimately lead to fragile and unre…
DOT: Dynamic Object Tracking for Visual SLAM
Irene Ballester, Alejandro Fontan, Javier Civera +2
In this paper we present DOT (Dynamic Object Tracking), a front-end that added to existing SLAM systems can significantly improve their robustness and accuracy in highly dynamic en…
Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments
Cedric Le Gentil, Mallikarjuna Vayugundla, Riccardo Giubilato +3
The ability to recognize previously mapped locations is an essential feature for autonomous systems. Unstructured planetary-like environments pose a major challenge to these system…
Learning Multiplicative Interactions with Bayesian Neural Networks for Visual-Inertial Odometry
Kashmira Shinde, Jongseok Lee, Matthias Humt +2
This paper presents an end-to-end multi-modal learning approach for monocular Visual-Inertial Odometry (VIO), which is specifically designed to exploit sensor complementarity in th…
Effective Version Space Reduction for Convolutional Neural Networks
Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel +1
In active learning, sampling bias could pose a serious inconsistency problem and hinder the algorithm from finding the optimal hypothesis. However, many methods for neural networks…
Estimating Model Uncertainty of Neural Networks in Sparse Information Form
Jongseok Lee, Matthias Humt, Jianxiang Feng +1
We present a sparse representation of model uncertainty for Deep Neural Networks (DNNs) where the parameter posterior is approximated with an inverse formulation of the Multivariat…