Shaoxiong Yao

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About

Shaoxiong Yao is a robotics researcher whose work centers on robotic manipulation, deformable object modeling, and agricultural automation. His key contributions lie in enabling robots to interact intelligently with complex, real-world objects—from soft, heterogeneous materials to occluded fruits in dense foliage. In his highly cited 2023 paper, "Estimating Tactile Models of Heterogeneous Deformable Objects in Real Time" (16 citations), Yao introduced a groundbreaking method that allows robots to learn the force response of deformable objects directly from sensor data, using a novel volumetric stiffness field representation. This work eliminates the need for prior knowledge, enabling real-time adaptation to unknown materials. More recently, in "Safe Leaf Manipulation for Accurate Shape and Pose Estimation of Occluded Fruits" (2025, 6 citations), Yao addresses a critical bottleneck in agricultural robotics: fruit occlusion. By developing a safe leaf manipulation strategy, his system actively moves foliage to improve fruit visibility, enhancing shape and pose estimation accuracy for automated crop monitoring. This work directly supports the growing demand for efficient, robot-driven agriculture. With a focus on sensor-driven learning and safe interaction, Yao’s research is shaping the future of autonomous systems in unstructured environments.