Autonomous Tractor Navigation in Orchard - Diagnosis and Supervision for Enhanced Availability

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Abstract

Autonomous vehicles require a very high degree of availability and safety to become accepted by authorities and the public. Diagnosis and supervision are necessary means to achieve this. This paper investigates ways of using laser-scanner data to do localisation, and as a source of independent supervision, using expectation maximisation of laser-scanner output against uncertain map features. Analysis of system behaviours and their structure shows which redundant information is available to construct a supervisor. Tests on real life orchard data demonstrates the feasibility of the new approach.
Original languageEnglish
Title of host publicationProcedings of 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
Publication date2009
Pages360-365
ISBN (Print)978-3-902661-46-3
DOIs
Publication statusPublished - 2009
Event7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes - Barcelona, Spain
Duration: 30 Jun 20093 Jul 2009
Conference number: 7
http://safeprocess09.upc.es/

Conference

Conference7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
Number7
CountrySpain
CityBarcelona
Period30/06/200903/07/2009
Internet address

Keywords

  • Autonomous vehicle
  • Structural analysis
  • Statistical methods

Cite this

Hansen, S., Blanke, M., & Andersen, J. C. (2009). Autonomous Tractor Navigation in Orchard - Diagnosis and Supervision for Enhanced Availability. In Procedings of 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes (pp. 360-365) https://doi.org/10.3182/20090630-4-ES-2003.00060