Title :
Fast vision-based localization for a mars airplane
Author :
Arai, Kenta ; Takamura, Hiroki ; Inoue, H. ; Ono, M. ; Adachi, Shuichi
Author_Institution :
Dept. of Appl. Phys. & Physico-Inf., Keio Univ., Yokohama, Japan
Abstract :
Mars airplane is one of the candidate payloads of JAXA´s next Mars exploration program. Airborne observation of Mars is expected to fill the “gap” between rovers, which provides a detailed observation but a limited area of coverage, and orbiters, which can cover a wide range of area but with a limited resolution. Two key challenges to realize a Mars airplane are 1) unavailability of GPS for localization and 2) limited computing power due to tight restriction on the mass of on-board instrument. We address these issues by developing a computationally tractable vision-based navigation algorithm. Our approach is based on an efficient feature detector and descriptor, Oriented FAST and Rotated BRIEF (ORB), combined with the information from an inertial measurement unit (IMU) using the extended Kalman filter (EKF) method. In this paper, we demonstrate the proposed ORB/EKF-based localization method by indoor experiments, using a small quadrotor helicopter and Mars surface image from Mars Reconnaissance Orbiter. The experimental results indicate that the computational cost of the proposed method is sufficiently small for real-time processing.
Keywords :
Global Positioning System; Kalman filters; Mars; aircraft control; aircraft navigation; autonomous aerial vehicles; feature extraction; helicopters; nonlinear filters; path planning; robot vision; GPS localization; IMU; JAXA Mars exploration program; Japan Aerospace Exploration Agency; Mars Reconnaissance Orbiter; Mars airplane; Mars surface image; ORB/EKF-based localization method; airborne observation; computational cost; computationally tractable vision-based navigation algorithm; computing power; extended Kalman filter; feature descriptor; feature detector; inertial measurement unit; on-board instrument; orbiters; oriented FAST and rotated BRIEF; rovers; small quadrotor helicopter; vision-based localization; Airplanes; Cameras; Extraterrestrial measurements; Feature extraction; Kalman filters; Mars; Robustness; Mars airplane; Terrain relative navigation; extended Kalman filter;
Conference_Titel :
SICE Annual Conference (SICE), 2014 Proceedings of the
Conference_Location :
Sapporo
DOI :
10.1109/SICE.2014.6935277