Title
GPU-Mapping: Robotic Map Building with Graphical Multiprocessors.
Abstract
This article provides a broad perspective of the potential applicability of graphical processing units (GPUs) computing power in robotics, specifically in the well-known problem of two-dimensional (2-D) robotic mapping. There are three possible ways of exploiting these massively parallel devices: 1) parallelizing existing algorithms, 2) integrating already existing parallelized general purpose software, and 3) use of its high-computational capabilities in the inception of new algorithms. This article presents examples for all three options: parallelizing a popular implementation of the gridmapping algorithm, using a GPU open-source linear sparse system solver to address the problem of linear least squares graph minimization, and developing a novel method that can be efficiently parallelized and executed in a GPU for handling overlapping grid maps in a mapping with local maps algorithm. Large speedups are shown in the experiments, highlighting the importance of this technology in robotic software development in the near future, as is already the case in many other areas.
Year
DOI
Venue
2013
10.1109/MRA.2012.2220503
IEEE Robot. Automat. Mag.
Keywords
Field
DocType
Graphics processing units,Simultaneous localization and mapping,Mobile robots,Cost function
Graph theory,Massively parallel,CUDA,Computer science,Parallel computing,Robotic mapping,Software,Computational science,Solver,Grid,Software development
Journal
Volume
Issue
ISSN
20
2
1070-9932
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Diego Rodríguez-losada115611.30
Pablo San Segundo221213.79
Miguel Hernando38910.11
Paloma de la Puente4699.93
Alberto Valero-Gomez5223.05