By Nola Taylor Redd -
The next mission to Mars could carry a smarter rover that is able to make better decisions absent instructions from Earth. Engineers are looking to automate some of the simple decision-making steps undertaken by rovers and orbiters, which could dramatically improve the science they are able to perform in the search for habitable environments.
“There are a lot of situations in which rovers can benefit from a little bit of extra onboard decision-making,” research technologist David Thompson of the Jet Propulsion Lab told Astrobiology Magazine.
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Ref: Spatio-spectral exploration combining in situ and remote measurements
Adaptive exploration uses active learning principles to improve the efficiency of autonomous robotic surveys. This work considers an important and understudied aspect of autonomous exploration: in situ validation of remote sensing measurements. We focus on high dimensional sensor data with a specific case study of spectroscopic mapping. A field robot refines an orbital image by measuring the surface at many wavelengths. We introduce a new objective function based on spectral un mixing that seeks pure spectral signatures to accurately model diluted remote signals. This objective re- flects physical properties of the multi-wavelength data. The rover visits locations that jointly improve its model of the environment while satisfying time and energy constraints. We simulate exploration using alternative planning approaches, and show proof of concept results with the canonical spectroscopic map of a mining district in Cuprite, Nevada.