Highly Accurate Obstacle Localization using Fused Inertial, RTK-GNSS, and Lidar Positioning for Agricultural Field Operations

Julian A.I. Lemke, Riikka Soitinaho, Timo Oksanen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Autonomous vehicles need to recognize and localize obstacles in their environment in order to avoid collisions. This paper presents a novel method for estimating the misalignment between a simultaneous localization and mapping (SLAM) map and and an Earth-fixed coordinate systems in order to allow highly accurate global localization of obstacles in the environment. The sensors used for this method are an Inertial Measurement Unit (IMU), satellite-based positioning (GNSS/GPS) and both 2D and 3D lidar sensors. Experimental validation on a tractor shows that the typical global localization accuracy is in the range of 100 mm…150 mm.

Original languageEnglish
Title of host publicationIFAC-PapersOnLine
EditorsHideaki Ishii, Yoshio Ebihara, Jun-ichi Imura, Masaki Yamakita
PublisherElsevier B.V.
Pages9269-9275
Number of pages7
Edition2
ISBN (Electronic)9781713872344
DOIs
StatePublished - 1 Jul 2023
Externally publishedYes
Event22nd IFAC World Congress - Yokohama, Japan
Duration: 9 Jul 202314 Jul 2023

Publication series

NameIFAC-PapersOnLine
Number2
Volume56
ISSN (Electronic)2405-8963

Conference

Conference22nd IFAC World Congress
Country/TerritoryJapan
CityYokohama
Period9/07/2314/07/23

Keywords

  • Field robotics
  • Perception
  • Precision agriculture
  • sensing

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