Xiangming Liu
Papers
2
Total Citations
10
H-Index
2
About
Xiangming Liu is a researcher in the field of bio-inspired robotics, with a primary focus on the energy-efficient locomotion of quadruped robots. His work centers on the critical challenge of optimizing gait parameters—the specific patterns of leg movement—to minimize energy consumption, a key factor for the practical deployment of legged robots in real-world environments. Liu’s major contributions include developing a novel design method for trotting gaits based on a single-leg dynamics model, which systematically analyzes the energy costs of support and swing phases. His most cited work, "Gait Parameters Design Method of Trotting Gait Based On Energy Consumption" (2021, 8 citations), provides a foundational framework for energy-aware gait design. Building on this, he has pioneered the use of reinforcement learning to automatically optimize gait parameters under a unified energy consumption index, as demonstrated in his 2022 paper. This integration of machine learning with classical dynamics represents a significant step toward adaptive, energy-efficient robotic locomotion. Liu’s research is particularly notable for its practical orientation, directly addressing the trade-offs between speed, stability, and power usage that are central to the future of autonomous legged systems.
Research Focus
Key Achievements
Top Papers
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