Jinjin Yan

UNSW Sydney, Harbin Engineering University

Papers

Total Citations

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About

Jinjin Yan is a leading researcher at the intersection of spatial navigation, autonomous systems, and robotic perception. Their work primarily focuses on developing flexible frameworks for seamless indoor/outdoor navigation, advancing multi-copter UAV swarm simulation, and pioneering event-driven tactile sensing for robotics. Yan’s most influential contribution is the “generic space definition framework” (2019, 45 citations), which enables humans and robots to navigate complex environments blending open, semi-open, and closed spaces—a critical step toward truly autonomous navigation in modern buildings. They also authored a comprehensive survey on open-source simulation platforms for multi-copter UAV swarms (2023, 16 citations), providing essential tools for cost-effective drone development. Yan’s innovative concept of “top-bounded spaces” (2019, 15 citations) introduced a novel least-top-exposed pathfinding approach, offering safer navigation alternatives in built environments. Most recently, their work on event-driven tactile sensing using dense spiking graph neural networks (2025, 5 citations) pushes the boundaries of robotic touch perception, enabling higher temporal resolution and energy efficiency for object recognition and grasping. With a growing citation impact and contributions spanning navigation theory, swarm robotics, and tactile AI, Jinjin Yan is shaping the future of intelligent, perceptive autonomous systems.