Papers
8
Total Citations
145
H-Index
5
About
Lin Xi is a robotics researcher whose work spans tactile sensing, autonomous navigation, and motion planning across land, sea, and air. Her most impactful contribution lies in robotic touch: she developed a novel tactile sensor that uses subtractive color mixing to detect surface friction and curvature, enabling robots to perceive slipperiness and local shape—critical for dexterous manipulation. This work, published in 2019, has garnered 70 citations and remains a key reference in the field. In parallel, Xi has advanced autonomous surface vehicle navigation by applying distributional reinforcement learning to COLREGs-compliant collision avoidance, a 2024 paper already earning 15 citations. She has also pioneered the first Gaussian process motion planning framework for 3D underwater environments, enabling unmanned underwater vehicles to navigate complex seafloor terrain and currents. Her research portfolio further includes improved artificial potential field methods for dynamic obstacle avoidance, neural network-based robot control, and decentralized multi-robot exploration under localization uncertainty. With over 145 total citations across her most-cited works, Lin Xi demonstrates a rare ability to bridge fundamental sensing challenges with practical, multi-domain autonomy—making her a rising figure in intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1Sensing the Frictional State of a Robotic Skin via Subtractive Color Mixing70 citations · 2019
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- 4An Improved APF Method for Complex and Dynamic Obstacles’ Avoidance13 citations · 2022
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