Edinburgh Research Explorer

Comparative Design Space Exploration of Dense and Semi-Dense SLAM

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • M. Zeeshan Zia
  • Luigi Nardi
  • Andrew Jackson
  • Emanuele Vespa
  • Bruno Bodin
  • Paul H.J. Kelly
  • Andrew J Davison

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Open

Documents

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7487261
Original languageEnglish
Title of host publication2016 IEEE International Conference on Robotics and Automation (ICRA)
PublisherIEEE
Pages1292 - 1299
Number of pages8
ISBN (Print)978-1-4673-8026-3
DOIs
StatePublished - May 2016

Abstract

SLAM has matured significantly over the past few years, and is beginning to appear in serious commercial products. While new SLAM systems are being proposed at every conference, evaluation is often restricted to qualitative visualizations or accuracy estimation against a ground truth. This is due to the lack of benchmarking methodologies which can holistically and quantitatively evaluate these systems. Further investigation at the level of individual kernels and parameter spaces of SLAM pipelines is non-existent, which is absolutely essential for systems research and integration. We extend the recently introduced SLAMBench framework to allow comparing two state-of-the-art SLAM pipelines, namely KinectFusion and LSD-SLAM, along the metrics of accuracy, energy consumption, and processing frame rate on two different hardware platforms, namely a desktop and an embedded device. We also analyze the pipelines at the level of individual kernels and explore their algorithmic and hardware design spaces for the first time, yielding valuable insights.

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