Alokesh Ghosh
Papers
3
Total Citations
33
H-Index
2
About
Alokesh Ghosh is a robotics and artificial intelligence researcher whose work is helping to transform agricultural automation, with a particular focus on the apple industry in Kashmir, India. His research bridges deep learning, robotic manipulation, and precision agriculture. Ghosh’s most influential contribution is a two-stage deep-learning model for detecting and occlusion-based classifying of Kashmiri orchard apples, designed specifically for robotic harvesting—a paper that has already garnered 22 citations since its 2023 publication. This work addresses a critical bottleneck in agricultural robotics: accurately identifying fruit in complex, cluttered orchard environments. He further advanced the field with an apple detection approach using the YOLOv8 algorithm, tailored to the unique conditions of Kashmir’s orchards, which are vital to the regional economy. Beyond agriculture, Ghosh has contributed to fundamental robotics, developing an ANFIS-based solution for inverse kinematics and forward dynamics of a 3-DOF serial manipulator. By integrating state-of-the-art computer vision with robotic control, Ghosh is not only advancing the science of autonomous harvesting but also providing practical, economically significant solutions for one of India’s key agricultural sectors.
Research Focus
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Top Papers
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