Enhancing Robot Capabilities of Environmental Perception through Embedded GPU

  • Marco Antonio Simoes Teixeira UTFPR
  • Nicolas Dalmedico UTFPR
  • Higor Barbosa Santos UTFPR
  • Andre Schneider De Oliveira UTFPR
  • Lucia Valeria Ramos De Arruda UTFPR
  • Flavio Neves UTFPR

Resumo


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.

Palavras-chave: Graphics processing units, Three-dimensional displays, Computer architecture, Robot sensing systems, Inspection, Robot Perception, Sensor Fusion, GPGPU, CUDA
Publicado
07/11/2017
TEIXEIRA, Marco Antonio Simoes; DALMEDICO, Nicolas; SANTOS, Higor Barbosa; OLIVEIRA, Andre Schneider De; ARRUDA, Lucia Valeria Ramos De; NEVES, Flavio. Enhancing Robot Capabilities of Environmental Perception through Embedded GPU. In: SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SISTEMAS COMPUTACIONAIS (SBESC), 7. , 2017, Curitiba/PR. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2017 . p. 217-224. ISSN 2237-5430.