Camera Localization in Outdoor Garden Environments Using Artificial Landmarks

Nicola Strisciuglio, Maria Leyva Vallina, Nicolai Petkov, Rafael Munoz Salinas

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

3 Citations (Scopus)


In this paper, we present an outdoor monocular camera localization system based on artificial markers and test its performance in one of the test gardens of the TrimBot2020 project, in Wageningen. We use ArUco markers to construct a map of the environment and to subsequently localize the camera position within it. We combine the localization algorithm based on ArUco with a Kalman filter to smooth the trajectory and improve the localization stability with respect to fast movements of the camera, and blurred or noisy images. We recorded two sequences, with resolution 480p and l080p respectively, in the TrimBot2020 garden. We compare the localization performance of ArUco with a keypoint-based approach, namely ORB-SLAM2. We analyze and discuss the strengths and problems of both marker- and keypoint-based approaches on the considered sequences. The performed comparison suggests that the two approaches might be fused to jointly improve re-localization and reduce the drift in pose estimation.

Original languageEnglish
Title of host publication2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings
Place of PublicationPiscataway, NJ
Number of pages6
ISBN (Electronic)978-1-5386-7506-9
ISBN (Print)978-1-5386-7507-6
Publication statusPublished - 12 Sept 2018
Externally publishedYes
Event2018 IEEE International Work Conference on Bio-inspired Intelligence, IWOBI 2018 - San Carlos, Costa Rica
Duration: 18 Jul 201820 Jul 2018


Conference2018 IEEE International Work Conference on Bio-inspired Intelligence, IWOBI 2018
Abbreviated titleIWOBI
Country/TerritoryCosta Rica
CitySan Carlos


  • Cameras
  • Kalman filters
  • Trajectory
  • Robot vision systems
  • Noise measurement
  • Pose estimation
  • Feature extraction


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