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- Creators: Barrett, The Honors College
Lunar Rover Navigation: Impact of Illumination Conditions on AI and Human Perception of Crater Sizes
When rover mission planners are laying out the path for their rover, they use a combination of stereo images and statistical and geological data in order to plot a course for the vehicle to follow for its mission. However, there is a lack of detailed images of the lunar surface that indicate the specific presence of hazards, such as craters, and the creation of such crater maps is time-consuming. There is also little known about how varying lighting conditions caused by the changing solar incidence angle affects perception as well. This paper addresses this issue by investigating how varying the incidence angle of the sun affects how well the human and AI can detect craters. It will also see how AI can accelerate the crater-mapping process, and how well it performs relative to a human annotating crater maps by hand. To accomplish this, several sets of images of the lunar surface were taken with varying incidence angles for the same spot and were annotated both by hand and by an AI. The results are observed, and then the AI performance was rated by calculating its resulting precision and recall, considering the human annotations as being the ground truth. It was found that there seems to be a maximum incidence angle for which detect rates are the highest, and that, at the moment, the AI’s detection of craters is poor, but it can be improved. With this, it can inform future and more expansive investigations into how lighting can affect the perception of hazards to rovers, as well as the role AI can play in creating these crater maps.
For this study, we used the Monte Carlo Neutral Particle Transport Code (MCNP6) to create a homogenous sphere that represented the PSRs on Moon, and then modeled five differing water contents for the lunar regolith ranging from 0-20 percent weight. These percent weights were modeled after the estimates for Shackleton crater, data from Lunar Reconnaissance Orbiter (LRO) mission, and data from Lunar Orbiter Laser Altimeter (LOLA).
This study was created with the LunaH-Map mission as motivation, seeking to exhibit what neutron data might be observed. The LunaH-Map mission is an array of mini-Neutron Spectrometers that will orbit the Moon 8-20 km away from the lunar surface and map the spatial
distribution of hydrogen at the lunar poles. The plots generated show the relationship between neutron flux and energy from the surface of the Moon as well as from 10km away. This data provides insight into the benefits of collecting orbital data versus surface data, as well as illustrating what LunaH-Map might observe within a PSR.