Hang Liu

Beijing University of Posts and Telecommunications, University of Michigan–Ann Arbor, Southeast University, Yunnan University

Papers

Total Citations

H-Index

About

Hang Liu is a pioneering researcher at the intersection of robotics, artificial intelligence, and intelligent materials, whose work spans from cloud-connected robotic systems to autonomous locomotion and environmental remediation. Liu’s key research areas include cloud robotics, legged locomotion in complex environments, and soft microrobotics. Their most cited work, “A Reinforcement Learning-Based Resource Allocation Scheme for Cloud Robotics” (2018, 52 citations), introduced a novel framework for offloading computationally intensive tasks from robots to the cloud, significantly advancing the efficiency of distributed robotic systems. In 2024, Liu published two highly impactful studies: “Quadruped robot traversing 3D complex environments with limited perception” (19 citations), which developed a method for legged robots to navigate challenging terrains without relying on external sensors—a breakthrough for operations in low-visibility conditions—and “A MXene Hydrogel‐Based Versatile Microrobot for Controllable Water Pollution Management” (17 citations), which created a multifunctional microrobot capable of remote navigation and rapid dye contaminant removal. Liu’s work also extends to robotic process automation, with their 2023 paper on attention-based automatic business process generation (7 citations). With over 95 total citations, Liu’s innovative contributions are shaping the future of autonomous systems and environmental robotics.