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Rosell-Polo, J.R., Llorens, J., Sanz-Cortiella, R., Arnó-Satorra, J., Ribes-Dasi, M., Masip, J., Escolà, A., Camp, F., Solanelles-Batlle, F., Gràcia, F., Gil, E., Val, L., Planas-Demartí, S. and Palacin-Roca, J. (2009) Obtaining the Three-Dimensional Structure of Tree Orchards from Remote 2D Terrestrial LIDAR Scanning. Agricultural and Forest Meteorology, 149, 1505-1515.
https://doi.org/10.1016/j.agrformet.2009.04.008

has been cited by the following article:

• TITLE: Simultaneous Localization and Mapping Solutions Using Monocular and Stereo Visual Sensors with Baseline Scaling System

  AUTHORS: Akram Afifi, Brendan Woo

  KEYWORDS: SLAM, Vision, Kalman Filter, Monocular, Stereo

  JOURNAL NAME: Positioning, Vol.10 No.4, October 16, 2019

  ABSTRACT: In this paper, SLAM systems are introduced using monocular and stereo visual sensors. The SLAM solutions are implemented in both indoor and outdoor. The SLAM samples have been taken in different modes, such as a straight line that enables us to measure the drift, in addition to the loop sample that is used to test the loop closure and its corresponding trajectory deformation. In order to verify the trajectory scale, a baseline method has been used. In addition, a ground truth has been captured for both indoor and outdoor samples to measure the biases and drifts caused by the SLAM solution. Both monocular and stereo SLAM data have been captured with the same visual sensors which in the stereo situation had a baseline of 20.00 cm. It has been shown that, the stereo SLAM localization results are 75% higher precision than the monocular SLAM solution. In addition, the indoor results of the monocular SLAM are more precise than the outdoor. However, the outdoor results of the stereo SLAM are more precise than the indoor results by 30%, which is a result of the small stereo baseline cameras. In the vertical SLAM localization component, the stereo SLAM generally shows 60% higher precision than the monocular SLAM results.