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About

Chao Qin is a robotics researcher whose work focuses on the critical challenge of autonomous navigation and control for aerial and ground robots. His primary research areas include visual servoing for aggressive quadrotor flight, lidar-inertial state estimation, and path tracking for multi-trailer mobile robots. Qin’s most impactful contribution is his 2023 paper on “Perception-Aware Image-Based Visual Servoing of Aggressive Quadrotor UAVs” (28 citations), which addresses the fundamental problem of maintaining visual features within the sensor field of view during high-speed maneuvers—a key bottleneck for underactuated aerial vehicles. He also developed LINS and R-LINS, two lidar-inertial state estimators (7 citations each) that provide robust, fast ego-motion estimation for autonomous robots by tightly coupling 3D lidar and IMU data using an iterated error-state Kalman filter. Earlier in his career, Qin contributed to path tracking control for tractor-trailer mobile robots using line-of-sight methods. His work bridges theoretical control design with practical implementation, offering solutions that enhance the reliability and agility of autonomous systems in challenging, dynamic environments.