Machine vision for autonomous small body navigation

This paper describes machine vision algorithms that enable precision guidance and hazard avoidance during small body exploration through onboard visual feature tracking and landmark recognition. These algorithms provide estimates of spacecraft relative motion and absolute position used to guide the spacecraft during autonomous landing and exploration. They also enable hazard avoidance by providing estimates of 3-D surface topography through processing of monocular image streams. This form of onboard autonomy is a critical enabling technology for multiple future missions including Comet Nucleus Sample Return, Large Asteroid Sample Return, Titan Organics Explorer and Europa Lander and Mars lander missions.