High-precision fruit localization using active laser-camera scanning: Robust laser line extraction for 2D-3D transformation

• DOI: 10.1016/j.atech.2023.100391
• Publication Date: 2024-01-04T19:03:03Z
• Authors: Pengyu Chu; Zhaojian Li; Kaixiang Zhang; Kyle Lammers; Renfu Lu
• Keywords: RGB color model; Laser Scanning; Digital camera

Recent advancements in deep learning-based approaches have led to remarkable progress fruit detection, enabling robust identification complex environments. However, much less has been made on 3D localization, which is equally crucial for robotic harvesting. Complex shape/orientation, clustering, varying lighting conditions, and occlusions by leaves branches greatly restricted existing sensors from achieving accurate localization the natural orchard environment. In this paper, we report design of a novel technique, called Active Laser-Camera Scanning (ALACS), achieve localization. The ALACS hardware setup comprises red line laser, an RGB color camera, linear motion slide, external RGB-D camera. Leveraging principles dynamic-targeting laser-triangulation, enables precise transformation projected 2D laser surface apples positions. To facilitate pattern acquisitions, Laser Line Extraction (LLE) method proposed high-precision feature extraction apples. Comprehensive evaluations LLE demonstrated its ability extract patterns under variable occlusion conditions. system achieved average apple accuracies 6.9 - 11.2 mm at distances ranging 1.0 m 1.6 m, compared 21.5 commercial RealSense indoor experiment. Orchard that 95% detachment rate versus 71% By overcoming challenges research contributes advancement harvesting technology.