Chuncheng Feng

Southwest University of Science and Technology, Tsinghua University

Papers

Total Citations

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About

Chuncheng Feng is a robotics researcher whose work bridges industrial manipulation and infrastructure inspection. His primary research areas include human-robot interaction, collision detection, and automated robotic inspection systems. Feng’s most impactful contribution is his 2018 paper on manipulator residual estimation for collision detection, which has garnered 20 citations. This work addresses a critical challenge in human-robot collaboration: improving sensitivity while reducing false alarms in collision detection, even when robot controllers have non-linear uncertainties. The method enhances safety and reliability in shared workspaces, making it valuable for manufacturing and service robotics. In 2019, Feng extended his expertise to civil infrastructure with a study on automated robotic inspection of diversion tunnel defects. This work demonstrated how robotic systems can replace dangerous manual inspections of hydropower tunnels, offering objective, efficient detection of hydraulic concrete defects that threaten structural safety. While less cited, this application-oriented research showcases Feng’s versatility in adapting robotic solutions to real-world engineering problems. His work contributes to making robots both safer collaborators and more capable inspectors, with implications for industrial automation and infrastructure maintenance.