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About

Benjamin McGuinness is a robotics researcher at the forefront of agricultural automation, specializing in computer vision, deep learning, and robotic manipulation for specialty crops. His work addresses critical labor shortages in horticulture by developing intelligent systems capable of complex, seasonal tasks. McGuinness’s most influential contribution, "Modelling wine grapevines for autonomous robotic cane pruning" (2023, 31 citations), tackles the challenge of training machines to make quality pruning decisions in New Zealand’s vital wine industry. He has also advanced robotic harvesting with key studies on asparagus spear detection using convolutional neural networks (2019, 14 citations) and a novel self-supervised method for determining apple ripeness under occlusion (2025, 7 citations). His research extends to practical localization systems using time-of-flight imaging for asparagus harvesting (2024, 3 citations) and the development of a versatile multipurpose robotic end effector capable of both fruitlet thinning and apple harvesting (2024, 3 citations). Through collaborations with the University of Waikato and Robotics Plus Limited, McGuinness is helping to build the next generation of autonomous agricultural robots, making skilled farm work more efficient and accessible.