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In this paper we introduce a general framework for an image based autonomous rock detection process for Martian terrain. A rock detection algorithm, based on this framework, is described and demonstrated on examples of real Mars Rover data. An attempt is made to produce a system that is independent of parameters to ease on-board implementation for real time(More)
—The Onboard Autonomous Science Investigation System (OASIS) evaluates geologic data gathered by a planetary rover. This analysis is used to prioritize the data for transmission, so that the data with the highest science value is transmitted to Earth. In addition, the onboard analysis results are used to identify science opportunities. A planning and(More)
The Autonomous Exploration for Gathering Increased Science (AEGIS) system enables automated data collection by planetary rovers. AEGIS software was uploaded to the Mars Exploration Rover (MER) mission’s Opportunity rover in December 2009 and has successfully demonstrated automated onboard targeting based on scientist-specified objectives. Prior to(More)
unknown environments where unexpected conditions can With each new rover mission to Mars, rovers are traveling significantly longer distances. In some cases, distances are increasing by orders of magnitude from previous missions. This increase enables not only the collection of more science data, but causes a large rise in the number of new and different(More)
The Autonomous Exploration for Gathering Increased Science (AEGIS) system provides automated data collection for planetary rovers. AEGIS was uploaded to the Mars Exploration Rover (MER) mission Opportunity rover in December 2009 to provide automated targeting capabilities for remote sensing instruments. Geological targets for rover remote-sensing(More)
The Onboard Autonomous Science Investigation System (OASIS) system has been developed to enable a rover to identify and react to serendipitous science opportunities. Using the FIDO rover in the Mars Yard at JPL, we have successfully demonstrated a fully autonomous opportunistic science system. The closed loop system tests included the rover acquiring image(More)
This study provides a numerical representation of contextual effects on the meanings of words, constructed from the order judgments of 19 subjects concerning the word "red" in 19 sentences. Subjects judged whether or not the red object mentioned in a sentence was redder than, less red than, or could be equally as red as the red object mentioned in each of(More)
—Rover traverse distances are increasing at a faster rate than downlink capacity is increasing. As this trend continues, the quantity of data that can be returned to Earth per meter traversed is reduced. The capacity of the rover to collect data, however, remains high. This circumstance leads to an opportunity to increase mission science return by carefully(More)
This paper presents technology for performing autonomous commanding of a planetary rover. Through the use of AI planning, scheduling and execution techniques, the OASIS autonomous science system provides capabilities for the automated generation of a rover activity plan based on science priorities, the handling of opportunistic science, including new(More)