wavemap
Fast, efficient and accurate multi-resolution, multi-sensor 3D occupancy mapping
Science Score: 65.0%
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 2 DOI reference(s) in README -
○Academic publication links
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○Committers with academic emails
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✓Institutional organization owner
Organization ethz-asl has institutional domain (www.asl.ethz.ch) -
○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.9%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
Fast, efficient and accurate multi-resolution, multi-sensor 3D occupancy mapping
Basic Info
- Host: GitHub
- Owner: ethz-asl
- License: bsd-3-clause
- Language: C++
- Default Branch: main
- Homepage: https://ethz-asl.github.io/wavemap/
- Size: 4.72 MB
Statistics
- Stars: 501
- Watchers: 19
- Forks: 48
- Open Issues: 10
- Releases: 22
Topics
Metadata Files
README.md
Wavemap
Hierarchical, multi-resolution volumetric mapping
Wavemap achieves state-of-the-art memory and computational efficiency by combining Haar wavelet compression and a coarse-to-fine measurement integration scheme. Advanced measurement models allow it to attain exceptionally high recall rates on challenging obstacles like thin objects.
The framework is very flexible and supports several data structures, measurement integration methods, and sensor models out of the box. The ROS interface can, for example, easily be configured to fuse multiple sensor inputs, such as a LiDAR configured with a range of 20m and several depth cameras up to a resolution of 1cm, into a single multi-resolution occupancy grid map.
Wavemap provides C++ and Python APIs and an interface to ROS1. The code is extensively tested on Intel, AMD and ARM CPUs on Ubuntu 20.04, 22.04 and 24.04. Example Docker files are available and documented in the installation instructions. We welcome contributions.
⭐ If you find wavemap useful, star it on GitHub to get notified of new releases!
Documentation
The framework's documentation is available on GitHub Pages for easy online access. A PDF version of each release’s documentation can also be found in the respective release notes.
Table of contents
Paper
A technical introduction to the theory behind wavemap is provided in our open-access RSS paper, available here. For a quick overview, watch the accompanying 5-minute presentation here.
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.
Please cite this paper when using wavemap for research.
APA-style:
Reijgwart, V., Cadena, C., Siegwart, R., & Ott, L. (2023). Efficient volumetric mapping of multi-scale environments using wavelet-based compression. Proceedings of Robotics: Science and Systems XIX. https://doi.org/10.15607/RSS.2023.XIX.065
BibTeX:
@INPROCEEDINGS{reijgwart2023wavemap,
author = {Reijgwart, Victor and Cadena, Cesar and Siegwart, Roland and Ott, Lionel},
journal = {Robotics: Science and Systems. Online Proceedings},
title = {Efficient volumetric mapping of multi-scale environments using wavelet-based compression},
year = {2023-07},
}
Note that the code has significantly improved since the paper was written. Wavemap is now up to 10x faster, thanks to new multi-threaded measurement integrators, and uses up to 50% less RAM, by virtue of new memory efficient data structures inspired by OpenVDB.
Owner
- Name: ETHZ ASL
- Login: ethz-asl
- Kind: organization
- Location: Zurich, Switzerland
- Website: http://www.asl.ethz.ch
- Repositories: 439
- Profile: https://github.com/ethz-asl
Citation (CITATION.cff)
cff-version: 1.2.0
preferred-citation:
title: "Efficient volumetric mapping of multi-scale environments using wavelet-based compression"
authors:
- family-names: Reijgwart
given-names: Victor
- family-names: Cadena
given-names: Cesar
- family-names: Siegwart
given-names: Roland
- family-names: Ott
given-names: Lionel
journal: "Robotics: Science and Systems"
year: "2023"
type: conference-paper
doi: "10.15607/RSS.2023.XIX.065"
url: https://www.roboticsproceedings.org/rss19/p065.pdf
codeurl: https://github.com/ethz-asl/wavemap
GitHub Events
Total
- Create event: 14
- Issues event: 5
- Release event: 2
- Watch event: 75
- Delete event: 14
- Issue comment event: 17
- Push event: 61
- Pull request review comment event: 15
- Pull request event: 17
- Pull request review event: 21
- Fork event: 15
Last Year
- Create event: 14
- Issues event: 5
- Release event: 2
- Watch event: 75
- Delete event: 14
- Issue comment event: 17
- Push event: 61
- Pull request review comment event: 15
- Pull request event: 17
- Pull request review event: 21
- Fork event: 15
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Victor Reijgwart | v****t@h****m | 1,200 |
| github-actions[bot] | 4****] | 13 |
| Lucas Walter | w****l@g****m | 3 |
| Alexander Stumpf | a****f@e****m | 3 |
| GitHub Actions | g****s@g****m | 2 |
| marcojob | 4****b | 1 |
| Sergei Sergienko | d****1@g****m | 1 |
| Helen Oleynikova | h****a@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 27
- Total pull requests: 51
- Average time to close issues: 27 days
- Average time to close pull requests: 27 days
- Total issue authors: 15
- Total pull request authors: 6
- Average comments per issue: 4.19
- Average comments per pull request: 0.96
- Merged pull requests: 45
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 7
- Pull requests: 10
- Average time to close issues: about 10 hours
- Average time to close pull requests: 6 days
- Issue authors: 6
- Pull request authors: 3
- Average comments per issue: 0.43
- Average comments per pull request: 0.6
- Merged pull requests: 7
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- astumpf (8)
- YoungCapta1n (4)
- victorreijgwart (2)
- lucascdlima (1)
- miguelcastillon (1)
- sverrevr (1)
- MihirDharmadhikari (1)
- Tfly6 (1)
- Aldhra (1)
- Nimaro76 (1)
- gyeongmin6099 (1)
- MrBoriska (1)
- Tacha-S (1)
- zy-cuhk (1)
- tarquai (1)
Pull Request Authors
- victorreijgwart (49)
- Divelix (4)
- astumpf (3)
- marcojob (2)
- helenol (1)
- lucasw (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
- Total downloads: unknown
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 22
proxy.golang.org: github.com/ethz-asl/wavemap
- Documentation: https://pkg.go.dev/github.com/ethz-asl/wavemap#section-documentation
- License: bsd-3-clause
-
Latest release: v2.2.1+incompatible
published about 1 year ago