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Grothendieck categories. --- Localization theory.

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Localization theory --- p-adic logarithms --- Whitehead groups

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Mobile robot platforms have a wide range of hardware configurations in order to ac‐complish challenging tasks and require an efficient and accurate localization systemto navigate in the environment. The objective of this work is the evaluation of the de‐veloped Dynamic Robot Localization (DRL) system in three computing platforms,with CPUs ranging from low to high end (Intel Atom, Core i5, and i7), in order to ana‐lyze the configurations that can be used to adjust the trade-offs between pose estima‐tion accuracy and the associated computing resources required. The DRL is capable ofperforming pose tracking and global pose estimation in both 3 and 6 Degrees of Free‐dom (DoF) using point cloud data retrieved from LIDARs and RGB-D cameras andachieved translation errors of less than 30 mm and rotation errors of less than 5° whenevaluated in three environments. The sensor data retrieved from three testing plat‐forms was processed and the detailed profiling results were analyzed. Besides poseestimation, the self-localization system is also able to perform mapping of the envi‐ronment with probabilistic integration or removal of geometry and can use surface re‐construction to minimize the impact of sensor noise. These abilities will allow the fastdeployment of mobile robots in dynamic environments.

Mobile robots --- Localization theory. --- Design and construction.

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Localization theory. --- Categories (Mathematics) --- Homotopy theory --- Nilpotent groups

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Shear (Mechanics) --- Titanium-aluminum-vanadium alloys --- Localization theory. --- Structure.