Yao Mao
Papers
2
Total Citations
7
H-Index
1
About
Yao Mao is a robotics researcher whose work focuses on advancing robot manipulation through tactile sensing and neural network-based control. His primary research areas include tactile feedback for deformable object interaction, zeroing neural networks for robotic manipulators, and human-robot interaction in delicate tasks. Mao’s most notable contribution is his 2023 paper on "Interaction Control for Tool Manipulation on Deformable Objects Using Tactile Feedback," which has garnered 6 citations and addresses a critical gap in robotics: enabling robots to perform vision-denied, touch-sensitive tasks like administering swab tests. This work highlights the importance of tactile information beyond the tool-in-hand for contact state estimation, drawing inspiration from human haptic perception. In 2025, Mao further advanced the field with his study on "Two novel harmonic-resistant zeroing neural networks for time-varying problems in robotic manipulators," demonstrating his commitment to solving real-world control challenges. His research has significant implications for medical robotics, manufacturing, and assistive technologies, where precise, adaptive manipulation is essential. Mao’s work stands out for its practical focus on overcoming sensory and computational limitations in robotic systems, making him a promising figure in the intersection of tactile sensing and intelligent control.
Research Focus
Key Achievements
Top Papers
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- 2