Papers
8
Total Citations
83
H-Index
5
About
Dr. Guangkui Song is a leading researcher in robotics, specializing in parallel mechanisms, exoskeleton systems, and bipedal locomotion. His work bridges high-precision industrial robotics and adaptive human-assistive technologies. Dr. Song’s most impactful contribution is a novel approach to enhancing the stiffness of heavy-load parallel robots through strategic component selection (2019, 32 citations), a critical advancement for manufacturing. He further advanced the field by developing a universal vibration modeling framework for space parallel robots using screw theory (2022, 16 citations), and extending this to defective parallel robots for aerospace machining (2023, 9 citations), directly addressing stringent aerospace tolerances. In rehabilitation robotics, Dr. Song created a Dynamic Movement Primitives-based parametric gait model for lower limb exoskeletons (2020, 10 citations), enabling adaptive, patient-specific walking patterns. His recent work includes terrain-adaptive control for exoskeletons in urban environments (2024, 7 citations) and energy-efficient walking via a parallel compliant leg (2023, 4 citations). Dr. Song also proposed the Cosine-law-based Spatially Quantized Gait for knee-stretched bipedal walking (2023, 4 citations), mimicking human gait efficiency. His interdisciplinary reach extends to human-robot interaction, exploring acceptance of assistive robots among older adults (2025). With a growing citation record and a focus on real-world impact, Dr. Song is shaping the future of both industrial and assistive robotics.
Research Focus
Key Achievements
Top Papers
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