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Currently, rovers can travel tens of meters per sol, but the next generation
of rovers is predicted to be able to traverse ten or more times as far. This
capability presents a situation in which the rover will be able to travel to places
about which it has no information and which it was not able to see at the beginning of the sol.
This presents us with not only an exciting opportunity but also several challenges. This situation will require the rover to use methods for performing
effective science when the rover has left the area that was initially visible and is out of contact
with scientists.
The "Science on the Fly" software consists of two principal parts, the science observer and the
science planner. The science observer acts as the rover's eyes and ears. The science
observer interprets sensor data to find possible targets of scientific value.
The other part, the science planner, takes the observations made by
the science observer and plans experiments that would be of maximum scientific
value.
Science Observer
The Science Observer serves two major roles: identifying targets of interest and
categorizing them into useful groups. For example, the most prominent targets for
geological study are rocks. When the science observer examines an image, it looks for
rocks using a "machine learning" algorithm that has been trained ahead of time to
recognize rock-like features. Then, it autonomously categorizes those rocks into groups
based on data it has seen before. In this manner, the Science Observer can recognize
novel rocks as well as perform automatic geological analyses. Besides rocks,
targets of scientific interest could include lichens or patches of soil.
Science Planner
The Science Planner enables the rover to react to new science
opportunities as it moves into unexplored areas. The Science Planner
accepts priorities from the science team, such as "carbonate rocks are
important to sample." Then, when the Science Observer detects a
high-priority, interesting feature, the Science Planner tries to make
a plan for getting more useful information about the feature. For
instance, it might move closer and examine the feature with its
fluorescence sensor to look for signs of life. It is not always easy to
generate this kind of plan because examining every interesting feature would
take far more time and energy than the rover has available.
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| This rock has lichen on it. Can the rover detect it? |
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| The rover detecting lichen. |
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| The rover uses segmentation to find rocks. |
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| These rocks were detected by the rover. |
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