Autonomous onboard traverse science system

The Onboard Autonomous Science Investigation System (OASIS) is a technology for increasing science return during rover traverses by prioritizing data onboard, and identifying and reacting to unanticipated science opportunities. Rovers of the future will have the capacity to collect more data than can be downlinked back to Earth. OASIS can increase mission science return by carefully selecting the data with the highest science interest for downlink. These rovers may also be required to traverse long distances with little to no interaction with the science team on Earth. OASIS can act as a geologist's assistant and can autonomously direct the rover to take additional measurements of "interesting" rocks. The importance of characterizing the terrain along these traverses, a study that is now becoming known as traverse science, increases with the distances the rover must travel. This paper provides a brief overview of the entire OASIS system and how it analyzes one type of data - grayscale images taken by the rover for engineering and hazard avoidance purposes. Although the OASIS system can apply the same type of analysis to different data types, such as color images, hyperspectral images or point spectrometer data, we will only focus on grayscale images here. The paper also describes the latest advances in two key aspects of the system: image prioritization and the science alert. In image prioritization, we combine the results from three distinct prioritization methods to arrive at an overall downlink ranking of the images collected during a traverse. The science alert is a capability that enables the rover to identify and react to a pre-specified, and scientifically significant, signature. Once this signature has been detected via the onboard science analysis component, the planning and scheduling module updates the rover command sequence to stop the traverse and signal Earth of the find. If there is sufficient time and onboard resources before the next downlink opportunity, additional data samples of the target may be autonomously collected.