Yuanhao Ding
Papers
3
Total Citations
36
H-Index
3
About
Yuanhao Ding is a researcher advancing the frontiers of autonomous logistics and multi-robot systems. His work centers on three key areas: last-mile delivery coordination, multi-robot path planning, and high-precision localization for unmanned ground vehicles (UGVs). In his most cited work (19 citations), Ding proposed a novel framework for autonomous last-mile delivery using multiple heterogeneous UGVs, addressing a critical bottleneck in modern e-commerce by enabling smart, cooperative logistics without human intervention. He further developed a genetic multi-robot path planning (GMPP) algorithm (9 citations), which optimizes safe, efficient routes in large, obstacle-rich environments—a significant step toward scalable multi-robot operations. To overcome GPS limitations, Ding also pioneered a UWB base station cluster localization method (8 citations) that provides centimeter-level accuracy for UGVs in GPS-denied settings, such as indoor warehouses or urban canyons. Collectively, his contributions demonstrate a cohesive vision: building robust, intelligent ground vehicle teams that can navigate and deliver autonomously in complex real-world scenarios. With over 36 citations across his core publications, Ding’s work is shaping the future of smart logistics and autonomous navigation.
Research Focus
Key Achievements
Top Papers
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