Yongsen Qin

Papers

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About

Yongsen Qin is a robotics researcher whose work centers on autonomous navigation, motion planning, and safe robot operation in complex, unstructured environments. His major contribution lies in developing history-aware, risk-averse planning frameworks that enable mobile robots to traverse unknown uneven terrain without relying on pre-built maps. In his highly cited 2024 paper, Qin introduced a layered pipeline that maintains a dynamically extended tree structure during navigation, allowing the robot to learn from past traversal data and anticipate hazards in real time. This approach significantly reduces the risk of tip-overs or entrapment in rough terrain, addressing a critical gap in field robotics. With 4 citations in a short time, his work is gaining traction among researchers in autonomous systems and off-road navigation. Qin’s research is particularly notable for its practical focus on mapless, real-world deployment, making it highly relevant for applications in search-and-rescue, planetary exploration, and agricultural robotics. His systematic integration of history-aware reasoning with local planning marks a thoughtful step toward truly autonomous robots capable of operating safely beyond structured environments.