Sheng Feng
Papers
7
Total Citations
101
H-Index
5
About
Sheng Feng’s research bridges the gap between autonomous robotics and intelligent sensor networks, with a focus on dynamic localization, wireless sensor deployment, and human-robot aesthetic interaction. His work addresses critical challenges in indoor and hostile environments where traditional positioning systems fail. Feng’s most cited paper, “Unknown hostile environment-oriented autonomous WSN deployment using a mobile robot” (2021, 33 citations), proposes a novel approach for deploying wireless sensor networks in dangerous or inaccessible areas. He further advanced robot self-localization through methods like grid-based improved maximum likelihood estimation (2014, 15 citations) and triangulation centroid estimation (2017), which enable robots to navigate network blind spots autonomously. Beyond positioning, Feng explores the intersection of robotics and art, developing feature fusion and hierarchical processing networks for automatic aesthetics evaluation of robotic dance poses (2018, 14 citations; 2022, 4 citations). This work integrates computer vision with artificial intelligence to enhance robots’ ability to perceive and generate aesthetically pleasing movements. With over 100 total citations, Feng’s contributions are valuable for researchers in autonomous navigation, disaster rescue robotics, and human-robot interaction, offering practical solutions for real-world deployment and creative robotic applications.
Research Focus
Key Achievements
Top Papers
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- 4Feature fusion based automatic aesthetics evaluation of robotic dance poses14 citations · 2018
- 5WSN Deployment and Localization Using a Mobile Agent11 citations · 2017
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