Susheng Ding

Papers

Total Citations

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About

Susheng Ding is a researcher specializing in autonomous robotics, multi-robot coordination, and intelligent logistics systems, with a focus on last-mile delivery solutions. Their major contributions lie in developing cooperative frameworks for heterogeneous unmanned ground vehicles (UGVs) to enhance efficiency and safety in complex environments. Notably, their most-cited work, "Autonomous Last-Mile Delivery Based on the Cooperation of Multiple Heterogeneous Unmanned Ground Vehicles" (2021, 19 citations), proposes a novel method that integrates multiple UGVs for smart logistics, addressing key challenges in e-commerce delivery. Additionally, Ding advanced multi-robot path planning with a genetic algorithm (GMPP) that optimizes routes in obstacle-rich settings (9 citations), and pioneered UWB-based localization for UGV guidance, offering a GPS-independent alternative for indoor or GNSS-denied environments (8 citations). Their research demonstrates significant impact in bridging theoretical algorithms with practical deployment, earning recognition for improving path safety, feasibility, and positioning accuracy. Ding’s work is instrumental for students and researchers exploring autonomous systems, multi-agent coordination, and real-world robotics applications.