LIDAR-based detection of furrows for agricultural robot autonomous navigation

• Luna-Santamaria, Javier ^[1] ; Martínez de Dios, José Ramiro ^[1] ; Ollero Baturone, Aníbal ^[1]
  1. [1] Universidad de Sevilla

     Universidad de Sevilla

     Sevilla, España

     
• Localización: XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja) / coord. por Carlos Balaguer Bernaldo de Quirós, José Manuel Andújar Márquez, Ramón Costa Castelló, C. Ocampo-Martínez, Juan Jesús Fernández Lozano, Matilde Santos Peñas, José Simó, Montserrat Gil Martínez, José Luis Calvo Rolle, Raúl Marín, Eduardo Rocón de Lima, Elisabet Estévez Estévez, Pedro Jesús Cabrera Santana, David Muñoz de la Peña Sequedo, José Luis Guzmán Sánchez, José Luis Pitarch Pérez, Óscar Reinoso García, Óscar Déniz Suárez, Emilio Jiménez Macías, Vanesa Loureiro-Vázquez, 2022, ISBN 978-84-9749-841-8, págs. 728-734
• Idioma: inglés
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• Resumen

  • Robust and accurate autonomous navigation is a main challenge in agricultural robotics. This paper presents a LIDAR-based processing system for autonomous robot navigation in crops with high vegetation density. The method detects and locates the crop furrows and provides them to the robot control system, which guides the robot such that its caterpillar tracks move along the furrows preventing damages in the crop. The proposed LIDAR-based processing pipeline includes various inconsistencies removal and template matching steps to deal with the high noise level of LIDAR scans. It has been implemented in C++ using ROS Noetic and validated in two different plantations with different crop growth status.