Yi Tao
Papers
4
Total Citations
45
H-Index
3
About
Yi Tao is a leading researcher in agricultural robotics, with a primary focus on autonomous grape harvesting in highly occluded environments. His work addresses one of the most challenging problems in precision agriculture: enabling robots to locate and pick fruit when stems and bunches are partially or fully hidden by foliage. Tao’s major contributions include the development of active vision strategies for view planning, where he has pioneered both geometric and reinforcement learning-based approaches to guide robotic cameras to optimal viewpoints. His paper “View Planning for Grape Harvesting Based on Active Vision Strategy Under Occlusion” (2024, 20 citations) and its follow-up using self-supervised deep reinforcement learning (2025, 4 citations) are foundational in this area. Additionally, Tao has advanced 3D perception through PointResNet, a feature-enhanced semantic segmentation model built on PointNet++ (2024, 19 citations), which enables accurate, collision-free grasping of grape bunches. His work, including earlier studies on multi-feature segmentation (2023, 2 citations), is critical for the future of agricultural automation, directly addressing the bottleneck of reliable fruit detection in unstructured, occluded environments.
Research Focus
Key Achievements
Top Papers
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