103 citations · 328 across the 79 of their papers we have counts for
8 papers · 2 filters
CenterGrasp: Object-Aware Implicit Representation Learning for Simultaneous Shape Reconstruction and 6-DoF Grasp Estimation
Eugenio Chisari, Nick Heppert, Tim Welschehold +2
Reliable object grasping is a crucial capability for autonomous robots. However, many existing grasping approaches focus on general clutter removal without explicitly modeling obje…
Online Estimation of Articulated Objects with Factor Graphs using Vision and Proprioceptive Sensing
Russell Buchanan, Adrian Röfer, João Moura +2
From dishwashers to cabinets, humans interact with articulated objects every day, and for a robot to assist in common manipulation tasks, it must learn a representation of articula…
A Smart Robotic System for Industrial Plant Supervision
D. Adriana Gómez-Rosal, Max Bergau, Georg K. J. Fischer +10
In today's chemical plants, human field operators perform frequent integrity checks to guarantee high safety standards, and thus are possibly the first to encounter dangerous opera…
Learning Hierarchical Interactive Multi-Object Search for Mobile Manipulation
Fabian Schmalstieg, Daniel Honerkamp, Tim Welschehold +1
Existing object-search approaches enable robots to search through free pathways, however, robots operating in unstructured human-centered environments frequently also have to manip…
Efficient Learning of Urban Driving Policies Using Bird's-Eye-View State Representations
Raphael Trumpp, Martin Büchner, Abhinav Valada +1
Autonomous driving involves complex decision-making in highly interactive environments, requiring thoughtful negotiation with other traffic participants. While reinforcement learni…
The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation
Jan Ole von Hartz, Eugenio Chisari, Tim Welschehold +3
In policy learning for robotic manipulation, sample efficiency is of paramount importance. Thus, learning and extracting more compact representations from camera observations is a…
CoVIO: Online Continual Learning for Visual-Inertial Odometry
Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard +1
Visual odometry is a fundamental task for many applications on mobile devices and robotic platforms. Since such applications are oftentimes not limited to predefined target domains…
CoDEPS: Online Continual Learning for Depth Estimation and Panoptic Segmentation
Niclas Vödisch, Kürsat Petek, Wolfram Burgard +1
Operating a robot in the open world requires a high level of robustness with respect to previously unseen environments. Optimally, the robot is able to adapt by itself to new condi…