Zhenjun Ying
Papers
1
Total Citations
23
H-Index
1
About
Zhenjun Ying is a robotics researcher whose work centers on multi-robot cooperation, relative pose estimation, and autonomous systems. His most notable contribution is the development of CREPES (Cooperative RElative Pose Estimation System), a novel approach that enables six degrees of freedom (DOF) mutual localization for multi-robot teams. This system, published in 2023 and already garnering 23 citations, employs a compact hardware design using active infrared LEDs and a fish-eye camera to achieve precise relative positioning—a critical capability for coordinated swarm operations. Ying’s work addresses fundamental challenges in collaborative robotics, where accurate inter-robot sensing is essential for tasks like formation control, cooperative manipulation, and exploration. By providing a practical, high-precision solution for mutual localization, his research has significant implications for advancing autonomous multi-robot systems in real-world environments. His contributions are particularly valuable for students and researchers working on multi-agent coordination, as CREPES offers a scalable and robust framework that bridges the gap between theoretical localization algorithms and deployable hardware systems.
Research Focus
Key Achievements
Top Papers
- 1CREPES: Cooperative RElative Pose Estimation System23 citations · 2023