Yuan Cheng

Papers

Total Citations

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About

Yuan Cheng is a researcher in mobile robotics and computer vision, with a focus on autonomous navigation and environmental perception. Their work centers on developing robust methods for robots to detect and avoid obstacles in unknown or dynamic environments. Cheng’s most cited paper, “A Motion Image Detection Method Based on the Inter-Frame Difference Method” (2014, 57 citations), introduces a hybrid detection model that combines frame difference and background subtraction techniques to precisely separate obstacles from the environment, enabling more accurate mathematical descriptions for mobile robot vision systems. This contribution is foundational for real-time target detection in autonomous platforms. In related work, “Mobile Robot Obstacle Avoidance Based on Multi-Sensor Information Fusion Technology” (2014, 2 citations) explores integrating multiple sensor inputs to enhance a robot’s environmental perception and decision-making capabilities. Cheng’s research addresses critical challenges in autonomous navigation, including dynamic decision-making, behavior control, and path planning. Their contributions support the development of intelligent mobile robots with richer perception and more independent operation, advancing the field of robotics and automation.