Xiaokai Liu

Chinese Academy of Sciences, Guangzhou Institute of Advanced Technology

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About

Dr. Xiaokai Liu is a leading researcher in intelligent robotics, with a primary focus on autonomous navigation and human-robot interaction. His most impactful work addresses fundamental challenges in path planning for mobile robots, particularly in complex and dynamic environments. Dr. Liu’s 2021 paper on an “Improved Artificial Potential Field and Dynamic Window Method for Amphibious Robot Fish Path Planning” (47 citations) is a cornerstone contribution, ingeniously resolving the classic “local minimum” and “unreachable target” problems that have long plagued traditional potential field methods. This work provides a robust framework for smooth, obstacle-free navigation in amphibious settings. More recently, Dr. Liu has advanced the field of human-machine integration with his 2024 study on “Mobile robot following method based on UWB and single-line lidar.” In this work, he developed a sophisticated decision module that leverages DBSCAN clustering for reliable target recognition, localization, and re-identification, even when the target is temporarily lost. By fusing ultra-wideband and lidar data, Dr. Liu’s approach enables robust and efficient autonomous following, directly contributing to safer and more intuitive collaborative robots. His research is instrumental in pushing the boundaries of practical, real-world robotic systems.