TY - JOUR
T1 - The MADMAX data set for visual-inertial rover navigation on Mars
AU - Meyer, Lukas
AU - Smíšek, Michal
AU - Fontan Villacampa, Alejandro
AU - Oliva Maza, Laura
AU - Medina, Daniel
AU - Schuster, Martin J.
AU - Steidle, Florian
AU - Vayugundla, Mallikarjuna
AU - Müller, Marcus G.
AU - Rebele, Bernhard
AU - Wedler, Armin
AU - Triebel, Rudolph
N1 - Publisher Copyright:
© 2021 The Authors. Journal of Field Robotics published by Wiley Periodicals LLC.
PY - 2021/9
Y1 - 2021/9
N2 - Planetary rovers increasingly rely on vision-based components for autonomous navigation and mapping. Developing and testing these components requires representative optical conditions, which can be achieved by either field testing at planetary analog sites on Earth or using prerecorded data sets from such locations. However, the availability of representative data is scarce and field testing in planetary analog sites requires a substantial financial investment and logistical overhead, and it entails the risk of damaging complex robotic systems. To address these issues, we use our compact human-portable DLR Sensor Unit for Planetary Exploration Rovers (SUPER) in the Moroccan desert to show resource-efficient field testing and make the resulting Morocco-Acquired data set of Mars-Analog eXploration (MADMAX) publicly accessible. The data set consists of 36 different navigation experiments, captured at eight Mars analog sites of widely varying environmental conditions. Its longest trajectory covers 1.5 km and the combined trajectory length is 9.2 km. The data set contains time-stamped recordings from monochrome stereo cameras, a color camera, omnidirectional cameras in stereo configuration, and from an inertial measurement unit. Additionally, we provide the ground truth in position and orientation together with the associated uncertainties, obtained by a real-time kinematic-based algorithm that fuses the global navigation satellite system data of two body antennas. Finally, we run two state-of-the-art navigation algorithms, ORB-SLAM2 and VINS-mono, on our data to evaluate their accuracy and to provide a baseline, which can be used as a performance reference of accuracy and robustness for other navigation algorithms. The data set can be accessed at https://rmc.dlr.de/morocco2018.
AB - Planetary rovers increasingly rely on vision-based components for autonomous navigation and mapping. Developing and testing these components requires representative optical conditions, which can be achieved by either field testing at planetary analog sites on Earth or using prerecorded data sets from such locations. However, the availability of representative data is scarce and field testing in planetary analog sites requires a substantial financial investment and logistical overhead, and it entails the risk of damaging complex robotic systems. To address these issues, we use our compact human-portable DLR Sensor Unit for Planetary Exploration Rovers (SUPER) in the Moroccan desert to show resource-efficient field testing and make the resulting Morocco-Acquired data set of Mars-Analog eXploration (MADMAX) publicly accessible. The data set consists of 36 different navigation experiments, captured at eight Mars analog sites of widely varying environmental conditions. Its longest trajectory covers 1.5 km and the combined trajectory length is 9.2 km. The data set contains time-stamped recordings from monochrome stereo cameras, a color camera, omnidirectional cameras in stereo configuration, and from an inertial measurement unit. Additionally, we provide the ground truth in position and orientation together with the associated uncertainties, obtained by a real-time kinematic-based algorithm that fuses the global navigation satellite system data of two body antennas. Finally, we run two state-of-the-art navigation algorithms, ORB-SLAM2 and VINS-mono, on our data to evaluate their accuracy and to provide a baseline, which can be used as a performance reference of accuracy and robustness for other navigation algorithms. The data set can be accessed at https://rmc.dlr.de/morocco2018.
KW - SLAM
KW - exploration
KW - extreme environments
KW - navigation
KW - planetary robotics
UR - http://www.scopus.com/inward/record.url?scp=85102772448&partnerID=8YFLogxK
U2 - 10.1002/rob.22016
DO - 10.1002/rob.22016
M3 - Article
AN - SCOPUS:85102772448
SN - 1556-4959
VL - 38
SP - 833
EP - 853
JO - Journal of Field Robotics
JF - Journal of Field Robotics
IS - 6
ER -