Surface-relative spacecraft navigation using computer vision
Planetary space exploration by unmanned missions strongly relies on automatic navigation. Computer vision has been recognized as a key to the feasibility of robust navigation, landing site identification and hazard avoidance. We are studying a scenario, where remote sensing methods from the orbit around the planet are used to preselect a landing site. The accuracy of the atmospheric entry is restricted by various parameters. One area of uncertainty results from inexact estimation of the landing position. The touch down point must be located an elliptic image area which is called the `ellipsis of uncertainty'. During landing, the early recognition of the preselected landing site in this image is an important factor. It improves the probability for a successful touchdown, since it allows real-time corrections of the trajectory to reach the planned touch down spot. We present a scenario that uses computer vision methods for this early identification emphasizing the phase between ten kilometers from ground and the identification of the lander position relative to the selected landing site.