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Fontoura, L.B
Furtado Jr, M.R
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Authors
Baltazar, J.D
Coelho, A.L
de Arruda Viana, L
Brandão, A.D
Valente, D.S
Furtado Jr, M.R
Fontoura, L.B
de Freitas, A
Farinati Leite, E
Valiati, J
Topics
Agricultural Robotics, Automation, and Mechanization
Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture
Type
Poster
Oral
Year
2026
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1. Performance of Autonomous Navigation in an Agricultural Tractor Using Pure Pursuit Control and Dubins Path Planning

Autopilot systems in agricultural machinery are primarily designed to ensure accurate tracking of predefined routes. However, their performance is strongly influenced by the internal parameters of the control algorithms employed, which may vary according to operational conditions. In this context, computational simulations constitute a valuable tool for investigating these interactions and identifying optimal operating configurations. This study evaluates an autopilot system based on the Pure... J.D. Baltazar, A.L. Coelho, L. De Arruda Viana, A.D. Brandão, D.S. Valente, M.R. Furtado Jr

2. From Render to Field: Detecting Asian Soybean Rust Using Models Trained Exclusively on Synthetic Imagery

Training machine learning models for crop disease detection requires large, annotated datasets that are costly and difficult to obtain under variable field conditions. Asian Soybean Rust (ASR) can reduce soybean yield by up to 90% and costs Brazilian producers over US$2 billion per season in fungicide applications and yield losses. Despite this impact, existing machine learning studies on ASR remain scarce with no publicly available RGB... L.B. Fontoura, A. De Freitas, E. Farinati Leite, J. Valiati