Tairan Chen

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About

Tairan Chen is a robotics researcher specializing in autonomous navigation for last-mile delivery systems, with a particular focus on sidewalk navigation in complex, real-world environments. His work addresses the critical challenge of enabling mobile robots to operate safely and reliably in pedestrian spaces where GPS signals are often unreliable and motion space is constrained. Chen’s major contributions include developing a robust sidewalk navigation method using sparse semantic point clouds, which enhances robot perception and localization in narrow, dynamic campus environments. His most-cited papers, "A Robust Sidewalk Navigation Method for Mobile Robots Based on Sparse Semantic Point Cloud" (13 citations) and "Vision Based Sidewalk Navigation for Last-mile Delivery Robot" (12 citations), demonstrate his systematic approach to overcoming appearance changes, unstable GPS, and narrow motion spaces through vision-based perception and semantic mapping. Chen’s work has significant implications for the practical deployment of autonomous delivery robots, offering a more reliable alternative to image-based and GPS-dependent systems. His research is particularly notable for its focus on real-world constraints, making his contributions highly relevant for students and researchers working on mobile robot navigation, autonomous logistics, and field robotics.