Kaijun Liu

National University of Singapore, Chongqing University

Papers

Total Citations

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About

Kaijun Liu is a researcher whose work bridges the critical gap between theoretical robotics and real-world deployment, with a particular focus on unmanned aerial vehicles (UAVs) and advanced optical sensing. His most influential contribution is the development of a high-fidelity quadrotor simulator using ROS and Gazebo, a tool that has garnered 32 citations by enabling researchers to safely test flight algorithms without the risks of physical prototypes. This work addresses a fundamental bottleneck in UAV development: the spatial and safety constraints of live flight testing. More recently, Liu has ventured into the frontier of optical fiber shape sensing, publishing a 2025 study on Monte Carlo-optimized spatial resolution in multi-channel parallel OFDR. This work, already accumulating 7 citations, targets the demanding requirements of minimally invasive surgical robotics and aerospace structural health monitoring. By pushing the limits of single-shot parallel measurement, Liu is helping to create the sensory backbone for next-generation medical and aerospace systems. His career trajectory—from accessible simulation tools to cutting-edge sensing hardware—demonstrates a rare ability to solve problems across the entire robotics stack, making his research equally valuable for students learning UAV control and engineers building the future of surgical robotics.