Feng Shen
Papers
5
Total Citations
37
H-Index
4
About
Feng Shen is a robotics researcher whose work focuses on intelligent path planning, environmental perception, and manipulator control for specialized robotic systems. His primary contributions lie in developing algorithms that enable robots to operate effectively in complex, constrained environments. Notably, his 2024 paper on an improved A-star path planning algorithm for mobile robots in medical testing laboratories has garnered 20 citations, addressing the critical need for efficient sample transport in healthcare settings. Shen has also advanced underground environmental perception using ground-penetrating radar for robotic systems, a relatively underexplored area with significant potential. In manipulator robotics, he has tackled challenging problems such as obstacle-avoidance inverse kinematics in overhead multi-line environments and fast collision detection using point clouds and stretched primitives, both published in 2024. His work on disparity estimation for electric inspection robots using lightweight neural networks further demonstrates his versatility. Through these contributions, Shen is helping to push the boundaries of robotic autonomy in specialized domains, from medical laboratories to infrastructure inspection.
Research Focus
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Top Papers
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