GPU acceleration in a visual servo system

Chuantao Zang, Koichi Hashimoto

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this paper we present our novel work of using the Graphic Processing Unit (GPU) to improve the performance of a homography-based visual servo system. We propose a GPU accelerated Efficient Second-order Minimization (GPU-ESM) algorithm to ensure a fast and stable homography solution, approximately 20 times faster than its CPU implementation. To enhance the system stability, we adopt a GPU accelerated Scale Invariant Feature Transform (SIFT) algorithm to deal with those cases where GPU-ESM algorithm performs poor, such as large image differences, occlusion and so on. The combination of both GPU accelerated algorithms is described in detail. The effectiveness of our GPU accelerated system is evaluated with experimental data. The key optimization techniques in our GPU applications are presented as a reference for other researchers.

Original languageEnglish
Pages (from-to)105-114
Number of pages10
JournalJournal of Robotics and Mechatronics
Volume24
Issue number1
DOIs
Publication statusPublished - 2012 Feb

Keywords

  • ESM
  • GPU acceleration
  • Homography
  • SIFT
  • Visual servo

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'GPU acceleration in a visual servo system'. Together they form a unique fingerprint.

  • Cite this