Papers
2
Total Citations
22
H-Index
2
About
Xiaofei Zhao is a robotics and manufacturing systems researcher whose work bridges mechanical design and optimization algorithms. His key research areas include bipedal locomotion, robotic cell scheduling, and bio-inspired optimization methods. Zhao’s most impactful contribution is his virtual-real gravity compensated inverted pendulum model for biped robots with heterogeneous legs, published in 2020 and cited 16 times. This work addresses the fundamental challenge of stable walking in robots with asymmetric limb configurations, offering a novel dynamic model validated through ADAMS simulation. In manufacturing systems, Zhao developed an effective chemical reaction optimization (ECRO) algorithm for cyclic multi-type parts robotic cell scheduling with blocking constraints. His approach simultaneously optimizes robotic move sequences and part input sequences using a new encoding method called robotic activity encoding, achieving significant efficiency gains in complex production environments. This work, cited 6 times, demonstrates Zhao’s ability to apply nature-inspired algorithms to real-world industrial problems. His research is particularly relevant for students and engineers working on legged robotics, production line automation, and metaheuristic optimization, where his models provide practical frameworks for improving system performance and stability.
Research Focus
Key Achievements
Top Papers
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