Yao Luo
Papers
2
Total Citations
3
H-Index
1
About
Yao Luo is a rising researcher in robotics, specializing in tactile perception, slip detection, and human–robot interaction. Their work addresses critical challenges in robotic manipulation and teleoperation, focusing on enabling stable grasping and intuitive control in dynamic environments. Luo’s most-cited paper, "Learning-Based Slip Detection and Fine Control Using the Tactile Sensor for Robot Stable Grasping" (2025, 2 citations), introduces a novel learning framework that leverages contrastive learning and feature alignment to enhance the accuracy of end-to-end slip detection, a key bottleneck for reliable robotic grasping. Another notable contribution, "An Intuitive and Efficient Teleoperation Human–Robot Interface Based on a Wearable Myoelectric Armband" (2025, 1 citation), proposes a wearable interface that allows users to seamlessly take over autonomous robots when they encounter complex or unpredictable scenarios. This work bridges the gap between autonomous capabilities and human oversight, improving safety and efficiency. Though early in their career, Luo’s research demonstrates significant potential for advancing dexterous manipulation and human–robot collaboration, with applications in manufacturing, assistive robotics, and beyond.
Research Focus
Key Achievements
Top Papers
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- 2