My work to date has been the design and implementation of a classifier capable of distinguishing rocks from meteorites, given input from multiple sensors, specifically a color camera and a reflectance spectrometer. To this end I have built a Bayes network based classifier that is capable of identifying different rock and meteorite types, and the process by which a rock sample was formed, in addition to the simpler task of discriminating between terrestrial rocks and meteorites. This classifier was designed and tested using spectral data and color imagery of rocks that I obtained in Antarctica in January 1998. Rigorous testing of the classifier is incomplete.
Results using the data used to train the classifier are excellent.
If this is so, it may be of little use in identifying previously unseen examples. It has only been evaluated on the data used to create it. Furthermore, the current data set is of limited size and was gathered using specific instruments similar but different to the ones that will be on the robot, and in acquired by a human operator in the field. Over a period of several weeks, weather permitting, the Nomad robot will be driven through the areas of Independence Moraine from where the data and rock samples were acquired last season. Images and spectral data from new samples will be collected, and fed to the classifier for assessment.