Vision-based navigation and guidance for small Mars UAVs

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 and guidance 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 simulations using image data from Mars Reconnaissance Orbiter, and obtain the result which is 4.4 times faster than a general method.

Keywords

• mars airplane
• vision-based localization
• feature detection
• extended kalman filter
• terrain relative navigation
• space robot
• image recognition
• navigation