The Visual–Inertial Canoe Dataset

Martin Miller, Soon Jo Chung, Seth Andrew Hutchinson

Research output: Contribution to journalArticlepeer-review

Abstract

We present a dataset collected from a canoe along the Sangamon River in Illinois. The canoe was equipped with a stereo camera, an inertial measurement unit (IMU), and a global positioning system (GPS) device, which provide visual data suitable for stereo or monocular applications, inertial measurements, and position data for ground truth. We recorded a canoe trip up and down the river for 44 minutes covering a 2.7 km round trip. The dataset adds to those previously recorded in unstructured environments and is unique in that it is recorded on a river, which provides its own set of challenges and constraints that are described in this paper. The dataset is stored on the Illinois Data Bank and can be accessed at: https://doi.org/10.13012/B2IDB-9342111_V1.

Original languageEnglish (US)
Pages (from-to)13-20
Number of pages8
JournalThe International Journal of Robotics Research
Volume37
Issue number1
DOIs
StatePublished - Jan 1 2018

Keywords

  • SLAM
  • dataset
  • stereo
  • inertial
  • IMU
  • monocular
  • vision
  • localization
  • mapping
  • robotics

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Mechanical Engineering
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Applied Mathematics

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