Zhenquan Fan

Papers

Total Citations

H-Index

About

Zhenquan Fan is a leading researcher in the field of robotic systems for hazardous environments, with a primary focus on search and rescue robotics and autonomous obstacle negotiation. His most impactful work, "Development of a search and rescue robot system for the underground building environment" (2023), has garnered 51 citations, establishing a foundational framework for deploying dual-robot teams in high-risk subterranean spaces such as burning or collapsed structures. Fan’s key contribution lies in designing systems that replace human first responders in dangerous underground scenarios, directly addressing a critical gap in urban disaster response. Expanding on this, his 2024 paper "Towards an obstacle detection system for robot obstacle negotiation" (17 citations) introduces an innovative elevation-map-based detection method capable of identifying positive, negative, and trench obstacles—a crucial advancement for enabling robots to autonomously navigate complex, debris-strewn terrains. By tackling the dual challenges of environmental perception and locomotion, Fan’s work pushes the boundaries of autonomous robotics, offering practical solutions for real-world emergencies. His research is essential reading for engineers and scientists developing resilient, perception-driven robots for disaster mitigation and urban infrastructure safety.