Paper Info
Title
Panoptic Multi-TSDFs: a Flexible Representation for Online Multi-resolution Volumetric Mapping and Long-term Dynamic Scene Consistency
Abstract
For robotic interaction in environments shared with other agents, access to volumetric and semantic maps of the scene is crucial. However, such environments are inevitably subject to long-term changes, which the map needs to account for. We thus propose panoptic multi-TSDFs as a novel representation for multi-resolution volumetric mapping in changing environments. By leveraging high-level information for 3D reconstruction, our proposed system allocates high resolution only where needed. Through reasoning on the object level, semantic consistency over time is achieved. This enables our method to maintain up-to-date reconstructions with high accuracy while improving coverage by incorporating previous data. We show in thorough experimental evaluation that our map can be efficiently constructed, maintained, and queried during online operation, and that the presented approach can operate robustly on real depth sensors using non-optimized panoptic segmentation as input.
Year
DOI
Venue
2022
10.1109/ICRA46639.2022.9811877
IEEE International Conference on Robotics and Automation
DocType
Volume
Issue
Conference
2022
1
Citations 
PageRank 
References 
0
0.34
0
Authors
7
Name
Order
Citations
PageRank
Lukas Schmid101.01
Jeffrey Delmerico200.34
Schonberger, J.L.326015.06
Juan I. Nieto493988.52
Marc Pollefeys57671475.90
Roland Siegwart67640551.49
Cesar Dario Cadena Lerma743730.12