Qingxi Liao
Papers
2
Total Citations
127
H-Index
2
About
Qingxi Liao is a researcher whose work bridges the frontiers of autonomous robotics and advanced photonic sensing. His key contributions lie in two distinct yet innovative areas: intelligent robotic navigation and flexible sensor technology. In robotics, Liao is best known for his pioneering application of Double Deep Q-Network (Double-DQN) reinforcement learning to path smoothing and tracking control for robotic vehicles. His 2019 paper on this method has garnered 107 citations, establishing a foundational approach for enabling more stable and adaptive autonomous navigation in complex environments. In the realm of photonics, Liao has made significant strides in developing flexible, stretchable photonic crystal sensors. His 2022 work, which has already earned 20 citations, introduces a nanograting structure fabricated via nanoreplica molding. This sensor achieves a remarkable biosensing sensitivity of 93 nm/RIU and demonstrates a tactile sensing resolution as fine as 0.1% strain. By integrating these capabilities, Liao’s research offers a versatile platform for both biomedical diagnostics and wearable haptic interfaces, showcasing his ability to drive impactful, cross-disciplinary innovation.
Research Focus
Key Achievements
Top Papers
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- 2