TODO: Table of Contents
MOROCCO 2018 Field Test —
The DLR Morocco-Acquired Dataset of Mars-Analogue eXploration (MADMAX)
List of all available Data. Locations A-H from the sites:
- Rissani 1 (N 31.2983, W 4.3871) –> A,B,C
- Kess Kess (N 31.3712, W 4.0518) –> D,E
- Maadid (N 31.5005, W 4.2202) –> F,G,H
Location Overview
Trajectories of the experiments together with the base station locations are shown in Openstreetmaps:
Please note that all presented data can be downloaded free of charge to be used in an academic environment.
However, registration is required to access the full list of download links.
Sensor Setup
| Sensor Type | Name | Specifications |
| Navigation Cameras | AlliedVision Mako G-319 | 4Hz, monochrome 1032 × 772px images, rectified |
| Color Camera | AlliedVision Mako G-319 | 4Hz, color 2064 × 1544px images, rectified |
| Camera Lenses | RICOH FL-HC0614-2M | 6mm, F/1.4 |
| Omnicam Cameras | AlliedVision Mako G-319 | 4-8Hz, monochrome 2064 × 1544px images |
| Omnicam Lens | Entaniya 280 Fisheye | 1.07mm, F/2.8, 280 ◦ × 360 ◦ field of view |
| IMU | XSENS MTi-10 IMU | MEMS-IMU, 100Hz, three-axis acceleration and three-axis angular velocities |
| GNSS receiver | Piksi Multi GNSS SwiftNav | 1Hz, GNSS Data |
| GNSS antenna | SwiftNav GPS500 | Frequencies: GPS L1/L2, GLONASS L1/L2 and Bei- Dou B1/B2/B3 |
Dataset Structure
All Data clustered by Location X and Run N.
Each Run X-N has the following data:
.
├── calibration.zip
│ ├── callab_camera_calibration_stereo.txt
│ ├── callab_camera_calibration_color.txt
│ ├── camera_rect_left_info.txt
│ ├── camera_rect_right_info.txt
│ ├── camera_rect_color_info.txt
│ ├── tf__T_to_B_init_pose.csv
│ ├── tf__IMU_to_camera_left.csv
│ ├── tf__IMU_to_camera_color.csv
│ ├── tf__IMU_to_camera_omni_up.csv
│ ├── tf__IMU_to_camera_omni_down.csv
│ └── tf__IMU_to_B.csv
│
├── ground_truth.zip
│ ├── gt_gnss.csv
│ ├── gnss_antenna_base
│ │ ├── gnss_base.obs
│ │ └── gnss_base.nav
│ ├── gnss_antenna_right
│ │ └── …
│ └── gnss_antenna_left
│ └── …
…
.
├── navigation_evaluation.zip
│ ├── orbslam2_nav.csv
│ ├── orbslam2_nav_aligned.csv
│ ├── vins_mono_nav.csv
│ └── vins_mono_nav_aligned.csv
│
├── imu_data.csv
│
├── metadata.txt
│
├── img_rect_left.zip
│ ├── img_rect_left_*.png
│ └── …
├── img_rect_right.zip
│ ├── img_rect_right_*.png
│ └── …
├── img_rect_color.zip
│ ├── img_rect_color_*.png
│ └── …
├── img_rect_depth.zip
│ ├── img_rect_depth_*.png
│ └── …
├── img_omni_up.zip
│ ├── img_omni_up_*.png
│ └── …
└── img_omni_down.zip
├── img_omni_down_*.png
└── …
Calibration
DLR CalDe and DLR CalLab – The open-source DLR Camera Calibration Toolbox
The calibration files contain images of the DLR calibration pattern seen by all cameras. The calibration images are found on the download page, together with the calibration results.
Provided files:
- raw images of the calibration pattern
- calibration results
- calibration information on the rectified images
TODO: BUTTON TO DOWNLOAD PAGE
Benchmark
We use the SLAM navigation algorithms VINS-Mono and ORB-SLAM2 for navigation with MADMAX. You are invited to compare your navigation solution against these to algorithms.
The code: VINS-Mono on Github.com
The paper: VINS-Mono: A Robust and Versatile MonocularVisual-Inertial State Estimator
The code: ORB-SLAM2 on Github.com
The paper: ORB-SLAM2: an Open-Source SLAM System forMonocular, Stereo and RGB-D Cameras
The navigation results are shown here:
TODO: CREATE RESULT PAGE
The resulting Data can be downloaded in the download section.
TODO: BUTTON TO DOWNLOAD PAGE
GNSS Ground Truth:
We computed the ground truth using our own algorithms. However, you can use the provided data of the left, right, and base antenna to compute your own ground truth.
The provided raw data can be processed using RTKLIB:
RTKLIB: An Open Source Program Package for GNSS Positioning
TODO: Upload image of GNSS Setup
Credits:
This work was funded by the DLR project MOdulares Robotisches EXplorationssystem (MOREX).
This activity has been conducted jointly with the two European Commission Horizon 2020 Projects InFuse and Facilitators. They received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 730068 and 730014.
If you use the data from the dataset in your own work, please cite us in the following way:
TODO
Publications:
TODO: List publications
- Our paper, once published
- LRU system Paper
- Other Morocco / PERASPERA papers
Statistics
TODO: Table with length, images lost, performance + error of ORB/VINS
Access
To gain access to the full list of sets please fill in.