Yinchen Liu

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About

Yinchen Liu is a leading researcher in robotics and control systems, with a primary focus on secure navigation and resilient autonomy in adversarial environments. His work addresses the critical challenge of ensuring safe robot operation when sensors and communication channels are compromised by malicious attacks. In his highly cited 2019 paper, "Secure trajectory planning against undetectable spoofing attacks" (49 citations), Liu developed novel algorithms that enable robots to plan trajectories that remain safe even when attackers inject false data into Global Navigation Satellite Systems (GNSS) without detection. His companion work, "Secure Navigation of Robots in Adversarial Environments" (29 citations), further advanced the field by integrating localization and path planning under unknown adversarial actions, considering robots with single integrator dynamics. These contributions are foundational for autonomous systems operating in hostile or untrusted settings, such as military drones, autonomous vehicles, and critical infrastructure robots. Liu's research has been instrumental in bridging the gap between control theory and cybersecurity, providing rigorous guarantees for robot safety against sophisticated spoofing attacks. His work continues to influence the design of resilient autonomous systems, making him a key figure in the emerging field of secure robotics.