Name
Title | ||
|---|---|---|
Vision-aided inertial navigation for pin-point landing using observations of mapped landmarks |
Abstract | ||
|---|---|---|
In this paper we describe an extended Kalman filter algorithm for estimating the pose and velocity of a spacecraft during entry, descent, and landing. The proposed estimator combines measurements of rotational velocity and acceleration from an inertial measurement unit (IMU) with observations of a priori mapped landmarks, such as craters or other visual features, that exist on the surface of a planet. The tight coupling of inertial sensory information with visual cues results in accurate, robust state estimates available at a high bandwidth. The dimensions of the landing uncertainty ellipses achieved by the proposed algorithm are three orders of magnitude smaller than those possible when relying exclusively on IMU integration. Extensive experimental and simulation results are presented, which demonstrate the applicability of the algorithm on real-world data and analyze the dependence of its accuracy on several system design parameters. (C) 2007 Wiley Periodicals, Inc. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1002/rob.20189 | JOURNAL OF FIELD ROBOTICS |
Keywords | Field | DocType |
inertial navigation,inertial measurement unit,tight coupling,land use,system design,visual cues,extended kalman filter | Inertial navigation system,Inertial frame of reference,Computer vision,Angular velocity,Simulation,A priori and a posteriori,Acceleration,Artificial intelligence,Inertial measurement unit,Engineering,Estimator,Spacecraft | Journal |
Volume | Issue | ISSN |
24 | 5 | 1556-4959 |
Citations | PageRank | References |
29 | 1.69 | 18 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikolas Trawny | 1 | 262 | 17.00 |
| Anastasios I. Mourikis | 2 | 1018 | 57.50 |
| Stergios I. Roumeliotis | 3 | 2124 | 151.96 |
| Andrew Johnson | 4 | 1489 | 95.14 |
| James F. Montgomery | 5 | 470 | 66.96 |