Abstract
This paper presents a navigation approach for autonomous agricultural robots based on LiDAR data. This navigation approach is divided into two parts: a line finding algorithm and a control algorithm. The paper proposes several line finding algorithms (based on PEARL/Ruby approach) that extract lines from a LiDAR data set. Once the lines have been processed from the data set, a control algorithm filters these lines and, using a fuzzy controller, generates the wheel speed commands to move the robot among the crop rows. This navigation approach was tested using a simulator built on ROS middle-ware and Gazebo (the source codes of the simulation are available on GitHub). The results of the simulated experiments show that the proposed approach performs well for a large range of crop configurations (with or without considering weeds, with or without holes in the crop rows…).
Funder
French “Pays de la Loire” region through the Atlanstic 2020 program
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Cited by
2 articles.
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