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About

Aarya Deb is a pioneering researcher in precision agriculture robotics, specializing in autonomous navigation, simultaneous localization and mapping (SLAM), and deep learning for in-row and under-canopy crop monitoring. Their major contributions center on the development of the Purdue AgBot (P-AgBot) platform, which integrates novel approaches for robotic physical sampling and leaf detection in dense cornfields. Deb’s work on P-AgSLAM introduced a robust SLAM framework that leverages 3D LiDAR data to enable accurate robot pose estimation under challenging canopy conditions, while P-AgNav advanced autonomous navigation through range view-based systems. Their deep learning-based leaf detection method further enhances robotic sampling efficiency, bridging IoT technologies with agricultural automation. With over 44 cumulative citations across their top papers, Deb’s research has significant impact on sustainable farming practices. Notably, their 2022 P-AgBot paper has garnered 19 citations, reflecting its foundational role in field robotics. Deb’s achievements include pioneering under-canopy navigation solutions that address critical gaps in agricultural monitoring, making their work essential for students and researchers advancing smart farming and autonomous systems.