Efficient volumetric mapping of multi-scale environments using wavelet-based compression
OPEN ACCESS
Loading...
Author / Producer
Date
2023-07
Publication Type
Conference Paper
ETH Bibliography
yes
Citations
Altmetric
OPEN ACCESS
Data
Rights / License
Abstract
Volumetric maps are widely used in robotics due to their desirable properties in applications such as path planning, exploration, and manipulation. Constant advances in mapping technologies are needed to keep up with the improvements in sensor technology, generating increasingly vast amounts of precise measurements. Handling this data in a computationally and memory-efficient manner is paramount to representing the environment at the desired scales and resolutions. In this work, we express the desirable properties of a volumetric mapping framework through the lens of multi-resolution analysis. This shows that wavelets are a natural foundation for hierarchical and multi-resolution volumetric mapping. Based on this insight we design an efficient mapping system that uses wavelet decomposition. The efficiency of the system enables the use of uncertainty-aware sensor models, improving the quality of the maps. Experiments on both synthetic and real-world data provide mapping accuracy and runtime performance comparisons with state-of-the-art methods on both RGB-D and 3D LiDAR data. The framework is open-sourced to allow the robotics community at large to explore this approach.
Permanent link
Publication status
published
External links
Book title
Proceedings of Robotics: Science and System XIX
Journal / series
Volume
Pages / Article No.
65
Publisher
Robotics Science & Systems Foundation
Event
Robotics: Science and Systems (RSS 2023)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Volumetric Mapping; Localization and Mapping; Robot State Estimation; Robot Perception; Sensors and Vision
Organisational unit
03737 - Siegwart, Roland Y. / Siegwart, Roland Y.
Notes
Funding
871542 - PILOTs for robotic INspection and maintenance Grounded on advanced intelligent platforms and prototype applications (EC)
Related publications and datasets
Is part of: https://www.roboticsproceedings.org/rss19