Max Robotics — Global Service Robot Directory + US Certification

About

Yinghua Fu is a leading researcher in agricultural robotics and embodied intelligence, with a focus on developing autonomous systems for complex, real-world manipulation tasks. Their most impactful work centers on two key areas: robotic harvesting for challenging agricultural environments and multi-embodiment robot learning benchmarks. Fu’s major contributions include the design and construction of a novel coconut picking robot that climbs trees to address severe labor shortages in Hainan’s coconut industry, a project that demonstrates practical engineering solutions for high-risk agricultural operations. Additionally, Fu co-created RoboMIND (Multi-embodiment Intelligence Normative Data for Robot Manipulation), a large-scale benchmark dataset containing 107,000 demonstration trajectories across 479 diverse tasks and 96 object classes. This resource, which has already garnered 14 citations in its 2025 version, is pivotal for advancing generalist robot manipulation by providing standardized training data across multiple robot embodiments. Fu’s work on integrating improved YOLOv8n-obb detection for oriented leaves and coconut clusters further showcases their expertise in combining computer vision with robotic systems. Through these contributions, Fu is shaping the future of both precision agriculture and multi-embodiment robot learning.