A robust obstacle detection method for robotic vacuum cleaners

Mun Cheon Kang, Kwang Shik Kim, Dong Ki Noh, Jong Woo Han, Sung-Jea Ko

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Conventional robotic vacuum cleaners (RVCs) with ultrasonic or infrared (IR) sensors present problems in detecting obstacles when they clean the floor in complex situations, for example, under tables or chairs with thin legs. This paper presents a robust obstacle detection (OD) method based on the triangulation principle for RVCs operating in various home environments. The proposed method uses the IR emitter of the RVC to project a horizontal IR beam toward the floor, following which the RVC's wide-angle vision camera captures an image that includes the IR line reflected by the floor or an obstacle. Obstacles are detected by using the image coordinates of the pixels that belong to the IR line in the captured image. Accurate separation of the IR line from the image background is accomplished by defining and minimizing an energy function based on the characteristics of the IR line. The proposed method was tested on the embedded RVC system and was shown capable of achieving OD performance compared with existing methods.

Original languageEnglish
Article number7027291
Pages (from-to)587-595
Number of pages9
JournalIEEE Transactions on Consumer Electronics
Volume60
Issue number4
DOIs
Publication statusPublished - 2014 Nov 1

Keywords

  • Image processing
  • line detection
  • obstacle detection
  • robotic vacuum cleaner

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Media Technology

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