A comparison of global localization algorithms for planetary exploration

Global localization of a planetary-exploration rover in the absence of a satellite-based global positioning system (GPS) is still an open problem. Although a satellite network is not available for localization around any near-term exploration targets, topographic maps derived from satellite imagery are available. This has spurred the development of several algorithms that perform global localization by matching data collected from onboard sensors to a global digital elevation map (DEM). This paper reviews two of these algorithms—Multiple-frame Odometry-compensated Global Alignment (MOGA) and VIsual Position Estimation for Rovers (VIPER)—and compares their performance on a common dataset, collected in a planetary analog environment. The comparison demonstrates the common factors limiting the performance of these algorithms, but also highlights the benefits and drawbacks of each method. Overall, the MOGA algorithm performed significantly better; however, running both algorithms is seen to be the best option as the computational cost of VIPER is low and it may succeed in some situations wherein MOGA will fail.

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