Description: Since Mars rovers have limited life span, NASA wants to maximize the exploration activities during this period. Rock sample analysis is one of the main tasks of rover missions. Traditionally, rock selection is decided by human operators. Due to long communication delay, manual selection process is time-consuming. There is a strong need to develop an automatic software system to automate the process. We propose a novel and high performance approach to enhancing rock selection process. We explicitly take advantage of the availability of LIBS instrument in the new generation of Mars rover. First, we use LIBS to quickly sample the neighborhood of the rover. LIBS can collect samples in seconds. Our software algorithms can quickly analyze the LIBS data and determine whether there are any interesting chemical elements. If yes, the APXS instrument will be activated. Otherwise, the rover will move to a new location and start the process again. In Phase I, we have demonstrated that our smart processing tools using actual Mars data and our results are more consistent than a current method. Moreover, our tools can implemented in a parallel processing system to achieve real-time performance. Our parallel processing system utilizes multi-core CPUs for distributed processing and we have used such processing architecture for speech and genomic processing.

Benefits: Our proposed algorithm can exactly meet the NASA's mission needs, including rover guidance, sample selection, and other scientific missions. We can handle different scenarios such as anomaly detection and supervised material identification. In Phase II, we also plan to embed our tools into JMARS, which allows users to use some postprocessing tools to analyze some database and further extract the composition of some rocks at different locations of MARS.

We expect to produce real-time tools containing the above mentioned algorithms for spectroscopy (LIBS and APXS) data processing. The tools can be useful for military surveillance and reconnaissance, and civilian applications (vegetation monitoring). Other applications include explosive detection, toxic industrious materials identification, environmental monitoring, soil quality monitoring, goal content assessment, and wood treatment processing control. The market size is estimated to be 20 million dollars over the next decade.