Zhen Ye
Papers
1
Total Citations
7
H-Index
1
About
Zhen Ye is a researcher advancing the frontier of multi-robot perception and 3D scene understanding. Their work focuses on enabling collaborative, communication-efficient mapping in unknown environments—a critical challenge for autonomous systems. Ye’s most impactful contribution, “MR-COGraphs,” introduces a novel framework that integrates foundation models with 3D scene graphs, allowing robots to share not just geometric data but also open-vocabulary semantic information. This breakthrough reduces communication overhead while preserving rich, contextual understanding, achieving 7 citations since its 2025 publication. By bridging the gap between large-scale AI models and practical multi-robot coordination, Ye’s research empowers systems to interpret and navigate complex environments with unprecedented flexibility. Their work stands out for tackling the dual challenges of scalability and semantic richness, offering a blueprint for future autonomous teams in search-and-rescue, exploration, and industrial inspection. Ye’s contributions are poised to influence how robots collaboratively perceive and act in the world, making them a rising voice in robotics and embodied AI.
Research Focus
Key Achievements
Top Papers
- 1