Geological Object Recognition in Extraterrestrial Environments
Abstract
On July 4 1997, the landing of NASA’s Pathnder probe and its rover Sojourner marked the beginning of a new era in space exploration; robots with the ability to move have made up the vanguard of human extraterrestrial exploration ever since. With Sojourners landing, for the rst time, a ground traversing robot was at a distance too far from earth to make direct human control practical. This has given rise to the development of autonomous systems to improve the e?ciency of these robots,in both their ability to move,and their ability to make decisions regarding their environment. Computer Vision comprises a large part of these autonomous systems, and in the course of performing these tasks a large number of images are taken for the purpose of navigation. The limited nature of the current Deep Space Network means that a majority of these images are never seen by human eyes. This work explores the possibility of using these images to target certain features by using a combination of three AdaBoost algorithms and established image feature approaches to help prioritize interesting subjects from an ever growing data set of imaging data.