Movatterモバイル変換

[0]ホーム
URL:

Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

 Sign up
Appearance settings

Commit0cfe714

Browse files
committed
Add a few more datasets.
1 parent72b846f commit0cfe714

File tree

3 files changed

+99
-0
lines changed

3 files changed

+99
-0
lines changed

‎_datasets/laser_registration.md‎

Lines changed: 35 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,35 @@
1+
---
2+
layout:dataset
3+
title:"Laser Registration Dataset"
4+
year:2013
5+
tags:[lidar, registration, mapping]
6+
eth_collection_url:"https://doi.org/10.3929/ethz-b-000721626"
7+
paper:"Laser-based Registration Methods for Outdoor Localization, ETH Zürich, Autonomous Systems Lab."
8+
doi:"10.3929/ethz-b-000721626"
9+
---
10+
11+
This dataset provides several real-world laser scans for testing and benchmarking**laser registration** and**outdoor localization** algorithms. The sequences include diverse outdoor environments containing buildings, vegetation, and long-range structures, suitable for evaluation of alignment, ICP-style registration, and mapping techniques.
12+
13+
##Data Access
14+
15+
The dataset is now hosted permanently on the**ETH Research Collection**:
16+
17+
➡️**Download / Landing Page:**
18+
**<https://doi.org/10.3929/ethz-b-000721626>**
19+
20+
##Contents
21+
22+
The dataset includes:
23+
24+
- 2D and 3D laser scans from outdoor scenes
25+
- Challenging environments with varying geometry
26+
- Ground truth / alignment information (depending on sequence)
27+
- Supporting information for evaluating registration performance
28+
29+
##Citation
30+
31+
If you use this dataset, please cite the ETH Research Collection entry:
32+
33+
>**Laser Registration Dataset**
34+
>Autonomous Systems Lab, ETH Zürich
35+
>DOI: 10.3929/ethz-b-000721626

‎_datasets/voxblox.md‎

Lines changed: 64 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,64 @@
1+
---
2+
layout:dataset
3+
title:"IROS 2017 – Voxblox Dataset"
4+
year:2017
5+
tags:[tsdf, esdf, mapping, reconstruction, planning, mav]
6+
eth_collection_url:"https://doi.org/10.3929/ethz-b-000721636"
7+
paper:"Helen Oleynikova, Zachary Taylor, Markus Fehr, Juan Nieto, Roland Siegwart – Voxblox: Incremental 3D Euclidean Signed Distance Fields for On-Board MAV Planning (IROS 2017)"
8+
doi:"10.3929/ethz-b-000721636"
9+
---
10+
11+
![Cow & Lady](/assets/datasets/voxblox/scene_photo.jpg)
12+
13+
14+
This dataset accompanies the**Voxblox** 3D volumetric mapping system, released in conjunction with the IROS 2017 paper*“Voxblox: Incremental 3D Euclidean Signed Distance Fields for On-board MAV Planning.”*
15+
16+
It provides RGB-D and/or depth-only sequences suitable for**TSDF/ESDF reconstruction**,**incremental mapping**, and**robotic planning** evaluation.
17+
18+
Original dataset page:
19+
https://projects.asl.ethz.ch/datasets/doku.php?id=iros2017
20+
21+
##Data Access
22+
23+
The dataset is now permanently hosted on the ETH Research Collection:
24+
25+
➡️**Download / Landing Page:**
26+
**<https://doi.org/10.3929/ethz-b-000721636>**
27+
28+
##Contents
29+
30+
The dataset includes sequences used for evaluating:
31+
32+
- voxel-based TSDF reconstruction
33+
- incremental ESDF generation
34+
- planning-aware mapping
35+
- online MAV/local robot navigation
36+
37+
Typical data provided:
38+
39+
- RGB–D recordings
40+
- depth images
41+
- calibrated intrinsic/extrinsic parameters
42+
- ground-truth or reference reconstructions (in some sequences)
43+
- example output reconstructions from Voxblox
44+
45+
##Paper
46+
47+
**Voxblox: Incremental 3D Euclidean Signed Distance Fields for On-board MAV Planning**
48+
Helen Oleynikova, Zachary Taylor, Markus Fehr, Juan Nieto, Roland Siegwart
49+
*IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017.*
50+
51+
GitHub:https://github.com/ethz-asl/voxblox
52+
53+
##BibTeX
54+
55+
<pre>
56+
@inproceedings{oleynikova2017voxblox,
57+
title = {Voxblox: Incremental {3D} Euclidean Signed Distance Fields for On-Board {MAV} Planning},
58+
author = {Oleynikova, Helen and Taylor, Zachary and Fehr, Markus and Nieto, Juan and Siegwart, Roland},
59+
booktitle = {2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
60+
pages = {1366--1373},
61+
year = {2017},
62+
organization = {IEEE}
63+
}
64+
</pre>
57.9 KB
Loading

0 commit comments

Comments
 (0)
[8]ページ先頭
©2009-2025 Movatter.jp