Omnidirectional-vision-based estimation for containment detection of a robotic mower

Junho Yang, Soon Jo Chung, Seth Hutchinson, David Johnson, Michio Kise

Research output: Contribution to journalConference articlepeer-review


In this paper, we present an omnidirectional-vision-based localization and mapping system which can detect whether a robotic mower is contained in a permitted area. We exploit a robot-centric mapping framework that exploits a differential equation of motion of the landmarks, which are referenced with respect to the robot body frame. The estimator in our system generates a 3D point-based map with landmarks. Concurrently, the estimator defines a boundary of the mowing area with the estimated trajectory of the mower. The estimated boundary and the landmark map are provided for the estimation of the mowing location and for the containment detection. We validate the effectiveness of our system through numerical simulations and present the results of the outdoor experiment that we conducted with our robotic mower.

Original languageEnglish (US)
Article number7140090
Pages (from-to)6344-6351
Number of pages8
JournalProceedings - IEEE International Conference on Robotics and Automation
Issue numberJune
StatePublished - Jun 29 2015
Externally publishedYes
Event2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States
Duration: May 26 2015May 30 2015

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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