-
Notifications
You must be signed in to change notification settings - Fork 915
/
boreas.yaml
49 lines (49 loc) · 2.93 KB
/
boreas.yaml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
Name: Boreas Autonomous Driving Dataset
Description: This autonomous driving dataset includes data from a 128-beam Velodyne Alpha-Prime lidar, a 5MP Blackfly camera, a 360-degree Navtech radar, and post-processed Applanix POS LV GNSS data. This dataset was collect in various weather conditions (sun, rain, snow) over the course of a year. The intended purpose of this dataset is to enable benchmarking of long-term all-weather odometry and metric localization across various sensor types. In the future, we hope to also support an object detection benchmark.
Documentation: https://github.com/utiasASRL/pyboreas/blob/master/DATA_REFERENCE.md
Contact: [email protected]
ManagedBy: "[ASRL](http://asrl.utias.utoronto.ca)"
UpdateFrequency: New driving sequences will be added as they are collected.
Tags:
- autonomous vehicles
- robotics
- computer vision
- lidar
- aws-pds
License: "[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/legalcode)"
Resources:
- Description: Boreas dataset
ARN: arn:aws:s3:::boreas
Region: us-west-2
Type: S3 Bucket
DataAtWork:
Tutorials:
- Title: Introduction to Visualizing Sensor Types (Jupyter notebook)
URL: https://github.com/utiasASRL/pyboreas/blob/master/pyboreas/tutorials/intro.ipynb
AuthorName: Keenan Burnett
Services:
- SageMaker
- Title: Project Lidar onto Camera Frames (Jupyter notebook)
URL: https://github.com/utiasASRL/pyboreas/blob/master/pyboreas/tutorials/lidar_camera_projection.ipynb
AuthorName: Keenan Burnett
Services:
- SageMaker
Publications:
- Title: Do we need to compensate for motion distortion and doppler effects in spinning radar navigation?
URL: https://www.dynsyslab.org/wp-content/papercite-data/pdf/burnett-ral21.pdf
AuthorName: K Burnett, A P Schoellig, T D Barfoot
- Title: Radar odometry combining probabilistic estimation and unsupervised feature learning
URL: https://arxiv.org/pdf/2105.14152.pdf
AuthorName: K Burnett, D J Yoon, A P Schoellig, T D Barfoot
- Title: "Boreas: A multi-season autonomous driving dataset"
URL: https://arxiv.org/abs/2203.10168
AuthorName: K Burnett, D J Yoon, Y Wu, A Z Li, H Zhang, S Lu, J Qian, W Tseng, A Lambert, K YK Leung, A P Schoellig, Timothy D Barfoot
- Title: Are We Ready for Radar to Replace Lidar in All-Weather Mapping and Localization?
URL: https://arxiv.org/abs/2203.10174
AuthorName: K Burnett, Y Wu, D J Yoon, A P Schoellig, T D Barfoot
- Title: "Picking up speed: Continuous-time Lidar-only odometry using doppler velocity measurements"
URL: https://arxiv.org/abs/2209.03304
AuthorName: Y Wu, D J Yoon, K Burnett, S Kammel, Y Chen, H Vhavle, T D Barfoot
- Title: "Need for Speed: Fast Correspondence-Free Lidar Odometry Using Doppler Velocity"
URL: https://arxiv.org/abs/2303.06511
AuthorName: D J Yoon, K Burnett, J Laconte, Y Chen, H Vhavle, S Kammel, J Reuther, T D Barfoot