Zeyang Qin
Papers
1
Total Citations
6
H-Index
1
About
Zeyang Qin is a researcher specializing in autonomous robotics and multi-vehicle localization systems, with a focus on enhancing navigation precision through sensor fusion. His most cited work, "Consistent Localization for Autonomous Robots With Inter-Vehicle GNSS Information Fusion" (2022), introduces a novel framework that leverages inter-vehicle GNSS data to improve localization accuracy. In this paper, Qin develops a hybrid GNSS filter (HGF) that integrates onboard sensor measurements with network-shared information, addressing critical consistency challenges in multi-robot systems. This contribution has garnered 6 citations, establishing a foundation for robust, decentralized navigation in dynamic environments. Qin's research bridges theoretical estimation theory and practical robotic applications, offering scalable solutions for autonomous fleets in GPS-denied or communication-constrained settings. His work is particularly relevant for advancing cooperative robotics in areas like search-and-rescue, precision agriculture, and autonomous logistics. By tackling the fundamental problem of consistent state estimation across distributed agents, Qin continues to influence the development of reliable, real-world autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1