Optical Navigation System for Pin-Point Lunar Landing

Abstract Major space agencies have an increasing interest in highly accurate (200 m) autonomous landing on the Moon. Inertial-only navigation is not compatible with this challenging requirement. The techniques currently investigated rely on vision-based navigation. A first approach consists in tracking features between sequences of images in order to measure the angular rate as well as the direction of the velocity vector of the spacecraft. A second approach aims at identifying image features using a geo-referenced on-board database to determine the attitude and the position of the spacecraft. However, existing algorithms are computationally prohibitive and have a limited robustness to varying illumination conditions and surface characteristics. This paper presents the development of an innovative autonomous vision-based navigation system addressing these problems. Numerical simulations have shown that this system is capable of estimating the position and velocity of the vehicle with an accuracy better than 100 m and 0.1 m/s respectively. This work is the result of a successful collaboration between the Universite de Sherbrooke, NGC Aerospace Ltd., Thales Alenia Space and the European Space Agency. The proposed system has been selected as the main navigation algorithm in three major research and development projects sponsored by European Space Agency and the Canadian Space Agency.

[1]  M. Dirk Robinson,et al.  Estimation theoretic analysis of motion in image sequences , 2004 .

[2]  A. D. Lewis.  The Maximum Principle of Pontryagin in control and in optimal control , 2006 .

[3]  Paul Winchester Chodas.  Combined satellite attitude and orbit determination with dynamic coupling , 1982 .

[4]  Augusto Caramagno,et al.  Design of Guidance and Control Algorithms for A Vi... , 2005 .

[5]  T. Brady,et al.  ALHAT System Architecture and Operational Concept , 2007, 2007 IEEE Aerospace Conference.

[6]  J. E. Riedel,et al.  Using Autonomous Navigation for Interplanetary Missions: Mission Operations with Deep Space 1 Autonav , 2000 .

[7]  Stephen Parkes,et al.  Planet Surface Simulation with PANGU , 2004 .

[8]  Masashi Uo,et al.  Optical Hybrid Navigation and Station Keeping around Itokawa , 2006 .

[9]  Stergios I. Roumeliotis,et al.  Vision-Aided Inertial Navigation for Spacecraft Entry, Descent, and Landing , 2009, IEEE Transactions on Robotics.

[10]  Stergios I. Roumeliotis,et al.  Vision‐aided inertial navigation for pin‐point landing using observations of mapped landmarks , 2007, J. Field Robotics.

[11]  A. Konopliv,et al.  Recent Gravity Models as a Result of the Lunar Prospector Mission , 2001 .

[12]  Larry H. Matthies,et al.  The Mars Exploration Rovers Descent Image Motion Estimation System , 2004, IEEE Intell. Syst..

[13]  J. Oberst,et al.  Lunar Global Shape and Polar Topography Derived from Kaguya-LALT Laser Altimetry , 2009, Science.

[14]  James R. Wertz,et al.  Spacecraft attitude determination and control , 1978 .

[15]  Philip N Springmann.  Lunar Descent Using Sequential Engine Shutdown , 2006 .

[16]  R. Smith,et al.  Space and planetary environment criteria guidelines for use in space vehicle development 1977 revision , 1983 .

[17]  Christian Philippe,et al.  The ESA Lunar Lander Mission , 2011 .