Ziran Liu

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About

Ziran Liu is a robotics researcher whose work focuses on making autonomous systems more robust and practical in real-world and space environments. His primary research areas include Task and Motion Planning (TAMP), model predictive control, and space robotics. Liu’s major contribution is the development of a modular multi-level replanning TAMP framework that enables robots to dynamically adapt their high-level logic and low-level motion plans to interference and control errors—a critical step toward deploying TAMP in unpredictable settings. This work has already garnered 11 citations since its 2024 publication. He has also advanced sequential manipulation for space robots with a priority-based switching model predictive control method, achieving efficient task execution with 6 citations in 2025. To bridge the gap between simulation and reality, Liu led the design and demonstration of an air-bearing-based space robot testbed, providing a valuable platform for validating complex planning and control algorithms for future on-orbit servicing and debris removal missions. His research is shaping the next generation of resilient, autonomous robots for both terrestrial and extraterrestrial applications.