Abstract
The automation of agricultural processes is expected to positively impact the environment by reducing waste and increasing food security, maximising resource use. Precision spraying is a method used to reduce the losses during pesticides application, reducing chemical residues in the soil. In this work, we developed a smart and novel electric sprayer that can be assembled on a robot. The sprayer has a crop perception system that calculates the leaf density based on a support vector machine (SVM) classifier using image histograms (local binary pattern (LBP), vegetation index, average, and hue). This density can then be used as a reference value to feed a controller that determines the air flow, the water rate, and the water density of the sprayer. This perception system was developed and tested with a created dataset available to the scientific community and represents a significant contribution. The results of the leaf density classifier show an accuracy score that varies between 80% and 85%. The conducted tests prove that the solution has the potential to increase the spraying accuracy and precision.
Highlights
IntroductionAgricultural land is limited and can only increase marginally, so we need to produce more with the same resources through higher precision, intelligent agriculture
Precision agriculture benefits the environment by reducing the quantities of pesticides applied and the resources spent on machinery
A robotic platform was adapted to work on complex terrain conditions and whose dimensions and locomotion mechanism allow tight manoeuvring in mountain vineyards with very narrow rows. This robot is equipped with advanced algorithms for self-localisation and navigating using light detection and ranging (LiDAR) sensors and Global Navigation Satellite System (GNSS) receiver data to support precision spraying tasks
Summary
Agricultural land is limited and can only increase marginally, so we need to produce more with the same resources through higher precision, intelligent agriculture. The use of tractors has low spraying efficiency due to off-target and soil compaction problems Inspired by this problem, in this work, we developed a modular and precision terrestrial sprayer robot, the Precision Robotic Sprayer (PRySM), which is capable of operating autonomously on rugged terrain with steep slopes and under the most diverse ground conditions. A robotic platform was adapted to work on complex terrain conditions and whose dimensions and locomotion mechanism allow tight manoeuvring in mountain vineyards with very narrow rows This robot is equipped with advanced algorithms for self-localisation and navigating using light detection and ranging (LiDAR) sensors and Global Navigation Satellite System (GNSS) receiver data to support precision spraying tasks.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
