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:

Vollbildanzeige

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.