Yingzhe Shen

University of Chinese Academy of Sciences

Papers

Total Citations

H-Index

About

Yingzhe Shen is a robotics researcher whose work centers on collaborative visual simultaneous localization and mapping (SLAM) for service robots. Their major contribution is the development of a novel framework that enables multiple robots to work together through an edge server, which maintains a centralized map database and performs global optimization. This system allows each robot to register to existing maps, update them, or build new ones using a unified interface—a critical advancement for real-world multi-robot coordination. The most-cited paper on this topic has garnered 23 citations, demonstrating its growing influence in the field. By addressing the challenges of scalability and consistency in multi-agent SLAM, Shen’s work directly supports the deployment of service robots in dynamic environments like warehouses, hospitals, and homes. Their research bridges the gap between individual robot autonomy and collaborative intelligence, offering a practical solution for teams of robots to share spatial understanding without redundant mapping efforts. This framework stands out for its emphasis on edge computing, reducing onboard processing demands while maintaining real-time performance—a key achievement for cost-effective and efficient robotic systems.