TY - JOUR
T1 - Introducing a globally consistent orbital-based localization system
AU - Boukas, Evangelos
AU - Gasteratos, Antonios
AU - Visentin, Gianfranco
PY - 2018/3/1
Y1 - 2018/3/1
N2 - In spite of the good performance of space exploratory missions, open issues still await to be solved. In autonomous or composite semi-autonomous exploration of planetary land surfaces, rover localization is such an issue. The rovers of these missions (e.g., the MER and MSL) navigate relatively to their landing spot, ignoring their exact position on the coordinate system defined for the celestial body they explore. However, future advanced missions, like the Mars Sample Return, will require the localization of rovers on a global frame rather than the arbitrarily defined landing frame. In this paper we attempt to retrieve the absolute rover's location by identifying matching Regions of Interest (ROIs) between orbital and land images. In particular, we propose a system comprising two parts, an offline and an onboard one, which functions as follows: in advance of the mission a Global ROI Network (GN) is built offline by investigating the satellite images near the predicted touchdown ellipse, while during the mission a Local ROI Network (LN) is constructed counting on the images acquired by the vision system of the rover along its traverse. The last procedure relies on the accurate VO-based relative rover localization. The LN is then paired with the GN through a modified 2D DARCES algorithm. The system has been assessed on real data collected by the ESA at the Atacama desert. The results demonstrate the system's potential to perform absolute localization, on condition that the area includes discriminative ROIs. The main contribution of this work is the enablement of global localization performed on contemporary rovers without requiring any additional hardware, such as long range LIDARs.
AB - In spite of the good performance of space exploratory missions, open issues still await to be solved. In autonomous or composite semi-autonomous exploration of planetary land surfaces, rover localization is such an issue. The rovers of these missions (e.g., the MER and MSL) navigate relatively to their landing spot, ignoring their exact position on the coordinate system defined for the celestial body they explore. However, future advanced missions, like the Mars Sample Return, will require the localization of rovers on a global frame rather than the arbitrarily defined landing frame. In this paper we attempt to retrieve the absolute rover's location by identifying matching Regions of Interest (ROIs) between orbital and land images. In particular, we propose a system comprising two parts, an offline and an onboard one, which functions as follows: in advance of the mission a Global ROI Network (GN) is built offline by investigating the satellite images near the predicted touchdown ellipse, while during the mission a Local ROI Network (LN) is constructed counting on the images acquired by the vision system of the rover along its traverse. The last procedure relies on the accurate VO-based relative rover localization. The LN is then paired with the GN through a modified 2D DARCES algorithm. The system has been assessed on real data collected by the ESA at the Atacama desert. The results demonstrate the system's potential to perform absolute localization, on condition that the area includes discriminative ROIs. The main contribution of this work is the enablement of global localization performed on contemporary rovers without requiring any additional hardware, such as long range LIDARs.
KW - autonomous exploration
KW - DARCES
KW - feature extraction
KW - global localization
KW - learning
KW - machine learning
KW - mobile robotics
KW - motion estimation
KW - perception
KW - planetary exploration
KW - planetary robotics
KW - position estimation
KW - robotics vision
KW - vision-based navigation
UR - http://www.scopus.com/inward/record.url?scp=85026372597&partnerID=8YFLogxK
U2 - 10.1002/rob.21739
DO - 10.1002/rob.21739
M3 - Journal article
AN - SCOPUS:85026372597
SN - 1556-4959
VL - 35
SP - 275
EP - 298
JO - Journal of Field Robotics
JF - Journal of Field Robotics
IS - 2
ER -