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About

Rahul Jangali is a pioneering roboticist whose work addresses critical labor shortages in New Zealand’s horticultural industries through intelligent automation. His research focuses on agricultural robotics, computer vision, and end-effector design, with applications spanning viticulture and orchard management. Jangali’s most impactful contribution is his 2023 paper on modelling wine grapevines for autonomous robotic cane pruning, which has garnered 31 citations and tackles the skilled labor crisis in New Zealand’s wine industry by enabling robots to make quality pruning decisions. He further advanced precision agriculture with his work on mapping apple fruitlets in commercial orchards, a foundational step for automated thinning. Notably, Jangali developed a novel multipurpose robotic end effector capable of both fruitlet thinning and harvesting, featuring vacuum suction and modular design for interchangeable tasks. His platform “Archie Snr” demonstrates the practical integration of these technologies for autonomous apple thinning. With a growing citation record and publications from 2023-2024, Jangali is establishing himself as a key innovator in agricultural robotics, directly addressing industry needs while pushing the boundaries of robotic perception and manipulation in complex, unstructured environments.