Jun-lang Yan
Papers
2
Total Citations
6
H-Index
2
About
Jun-lang Yan is a researcher whose work bridges robotics, optimization, and human–machine interaction. His primary research areas include intelligent path planning, swarm intelligence algorithms, and assistive robotics for mobility-impaired individuals. Yan’s major contribution lies in developing novel computational models for escort robots operating in complex, real-world environments such as residential communities. He proposed an Improved Quantum Particle Swarm Optimization (IQPSO) algorithm to solve the NP-hard path planning problem, representing robot workspace as a grid graph for more efficient navigation. This work, cited 4 times, addresses a critical challenge in service robotics. Additionally, Yan explored deep learning-based gesture recognition for interactive control of intelligent wheelchairs, advancing accessible assistive technology. His research demonstrates a commitment to making autonomous systems more practical and user-friendly, with potential applications in healthcare and eldercare. Yan’s work continues to influence the development of intelligent, adaptive robots that can safely and effectively operate in human-centered environments.
Research Focus
Key Achievements
Top Papers
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