Bashan Zuo

Papers

Total Citations

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About

Bashan Zuo is a robotics researcher whose work focuses on the intersection of computer vision, control systems, and machine learning for autonomous manipulation and navigation. His primary contributions lie in developing robust visual servoing and grasping systems, where he pioneered a hybrid camera configuration that combines an eye-in-hand camera for precise tracking with a fixed external camera for broader spatial awareness. This approach, detailed in his most cited work (2014, 36 citations), significantly improves the reliability of robotic grasping in unstructured environments. Zuo also made notable advances in autonomous navigation by applying reinforcement learning—specifically Q-learning—to enable robots to adaptively learn navigation skills in unknown settings (2014, 30 citations). His research addresses critical challenges in space exploration and service robotics, where vision-based systems must operate with high precision and adaptability. While his citation counts reflect a focused and emerging impact, Zuo’s work demonstrates a clear trajectory toward integrating learning-based methods with classical control, offering practical solutions for real-world robotic autonomy.