12 citations · 42 across the 12 of their papers we have counts for
22 papers
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…
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 (…
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…