Simultaneous Localization and Mapping (SLAM)

This seminar explores why standard GNSS is insufficient for precision agriculture and how Simultaneous Localization and Mapping (SLAM) bridges the gap. Eurecat explains the evolution of SLAM algorithms—from Extended Kalman Filters to modern Graph SLAM—and addresses specific agricultural challenges like the “Green Desert” problem, visual aliasing, and seasonality. Learn how Semantic SLAM and sensor fusion enable autonomous tractors and robots to navigate complex environments (like greenhouses and orchards) where GPS often fails.