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About

Lanping Chen is a robotics researcher whose work centers on intelligent perception, motion control, and autonomous navigation for mobile and industrial robotic systems. Her most cited paper, "Research on obstacle avoidance for mobile robot based on binocular stereo vision and infrared ranging" (2011, 9 citations), introduces a multi-sensor fusion approach that combines infrared ranging with binocular vision to provide real-time, complete distance information for obstacle avoidance—a foundational contribution to safe autonomous navigation. Chen has also advanced robust control for robotic manipulators, proposing a variable structure control with feedforward compensator to handle load uncertainties and improve tracking precision (2010, 5 citations). In applied robotics, she designed a smart paint robot that leverages image processing and the Edge Drawing algorithm to capture clear contours for automated painting (2017, 4 citations). Her work on fuzzy planners for wheeled mobile robots (2011, 3 citations) further demonstrates her commitment to adaptive, sensor-driven navigation in unknown environments. More recently, Chen has explored trajectory prediction using adversarial learning with knowledge-rich latent variables (2020, 3 citations), signaling a move toward data-driven, predictive autonomy. With a career spanning sensor fusion, robust control, and intelligent planning, Chen’s research has laid practical groundwork for safer, more capable robots in both industrial and unstructured settings.