Yangqi Ou

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About

Yangqi Ou is a robotics researcher whose work centers on autonomous navigation, path planning, and simultaneous localization and mapping (SLAM) for mobile robots in complex, real-world environments. Ou’s most impactful contribution to date is the development of an improved A* path planning algorithm, detailed in a 2022 paper that has already garnered 75 citations. This work directly addresses a critical limitation of the traditional A* method—excessive turning points and slow search speeds—by proposing a more efficient, grid-based approach. The algorithm was validated on a mobile robot platform equipped with lidar and inertial measurement units, demonstrating its practical utility for obstacle-dense spaces. More recently, Ou has advanced the field of multi-sensor fusion with a 2025 study on lidar-inertial-wheel SLAM for ground robots. This work tackles the persistent challenge of error accumulation in feature-poor environments, where standard IMU-based methods falter, thereby enhancing reliability for applications like warehouse logistics and search-and-rescue. By integrating wheel odometry with lidar and inertial data, Ou’s research pushes toward more robust, drift-resistant navigation systems, marking a significant step forward for autonomous ground vehicles operating under demanding conditions.