TY - GEN
T1 - Vision-aided inertial navigation for precise planetary landing
T2 - 3rd International Conference on Robotics Science and Systems, RSS 2007
AU - Mourikis, Anastasios I.
AU - Trawny, Nikolas
AU - Roumeliotis, Stergios I.
AU - Johnson, Andrew
AU - Matthies, Larry
PY - 2008
Y1 - 2008
N2 - In this paper, we present the analysis and experimentalvalidation of a vision-aided inertial navigation algorithmfor planetary landing applications. The system employs tightintegration of inertial and visual feature measurements to computeaccurate estimates of the lander's terrain-relative position,attitude, and velocity in real time. Two types of features areconsidered: mapped landmarks, i.e., features whose global 3D positionscan be determined from a surface map, and opportunisticfeatures, i.e., features that can be tracked in consecutive images,but whose 3D positions are not known. Both types of features areprocessed in an extended Kalman filter (EKF) estimator and areoptimally fused with measurements from an inertial measurementunit (IMU). Results from a sounding rocket test, covering thedynamic profile of typical planetary landing scenarios, showestimation errors of magnitude 0.16 m/s in velocity and 6.4 min position at touchdown. These results vastly improve currentstate of the art for non-vision based EDL navigation, and meetthe requirements of future planetary exploration missions.
AB - In this paper, we present the analysis and experimentalvalidation of a vision-aided inertial navigation algorithmfor planetary landing applications. The system employs tightintegration of inertial and visual feature measurements to computeaccurate estimates of the lander's terrain-relative position,attitude, and velocity in real time. Two types of features areconsidered: mapped landmarks, i.e., features whose global 3D positionscan be determined from a surface map, and opportunisticfeatures, i.e., features that can be tracked in consecutive images,but whose 3D positions are not known. Both types of features areprocessed in an extended Kalman filter (EKF) estimator and areoptimally fused with measurements from an inertial measurementunit (IMU). Results from a sounding rocket test, covering thedynamic profile of typical planetary landing scenarios, showestimation errors of magnitude 0.16 m/s in velocity and 6.4 min position at touchdown. These results vastly improve currentstate of the art for non-vision based EDL navigation, and meetthe requirements of future planetary exploration missions.
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U2 - 10.15607/rss.2007.iii.019
DO - 10.15607/rss.2007.iii.019
M3 - Conference contribution
AN - SCOPUS:84959279482
SN - 9780262524841
T3 - Robotics: Science and Systems
SP - 145
EP - 152
BT - Robotics
A2 - Burgard, Wolfram
A2 - Brock, Oliver
A2 - Stachniss, Cyrill
PB - MIT Press Journals
Y2 - 27 June 2007 through 30 June 2007
ER -