Enhancing Robot Capabilities of Environmental Perception through Embedded GPU

摘要

The use of GPU in point cloud processing usually represents a gain in computation time more than ten times higher then on CPU, especially for large amounts of data. This paper brings an evaluation of the processing time for point cloud fusion in three different systems (PC, Nvidia TX1 and Nvidia TK1) using CPU and GPU. The objective is to find the best way to perform sensor fusion for an autonomous inspection robot. Four different scenarios were considered for the tests, with five different neighbor radius. A table with the processing time found for each experiment was created to allow a quick comparison. As results, a reduction in the number of points of up to 82.3 times was obtained, besides a time difference between CPU and GPU of up to 160 times.