Sanpeng Deng

Beijing Institute of Technology, Tianjin University of Technology and Education

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About

Sanpeng Deng is a robotics researcher whose work focuses on the design, control, and fault prediction of industrial and mobile robotic systems. His key research areas include robot trajectory tracking, intelligent control strategies, and autonomous cleaning systems. Deng’s most cited work, "Research on the oil tank sludge cleaning robot system" (2010, 14 citations), addresses the critical need for safer and more efficient automated cleaning of oil storage tanks, replacing hazardous manual operations. He has since advanced the field of mobile robotics by proposing a novel trajectory tracking method for non-holonomic wheeled robots that integrates fuzzy PID control with the Twin Delayed Deep Deterministic Policy Gradient (TD3) reinforcement learning algorithm, significantly improving accuracy and robustness. Deng has also contributed to the development of distributed drive articulated robots for rock-drilling applications, designing a steering control strategy based on push rod pose feedback. Additionally, his research applies self-organized critical theory to predict faults in industrial robots, aiming to reduce maintenance costs and downtime. Through these contributions, Deng demonstrates a sustained commitment to enhancing robot autonomy, safety, and reliability in complex real-world environments.