Papers
2
Total Citations
15
H-Index
2
About
Dr. Tian Song is a pioneering researcher at the intersection of medical robotics and intelligent control systems. Her work primarily focuses on advancing robot-assisted surgery through enhanced 3D visualization and improving the motion precision of omnidirectional mobile robots. Dr. Song’s most influential contribution, "Comparison of medical image 3D reconstruction rendering methods for robot-assisted surgery" (2017, 13 citations), established a critical framework for selecting optimal real-time visualization techniques, directly impacting the accuracy of disease detection and surgical outcomes. This foundational study remains a key reference for researchers developing next-generation surgical robots. More recently, Dr. Song has tackled the challenge of motion control in complex environments with her 2025 paper on "Sliding Mode Control of the MY-3 Omnidirectional Mobile Robot Based on RBF Neural Networks" (2 citations). This work introduces a novel hybrid control strategy that integrates sliding mode control with radial basis function neural networks to compensate for structural and systemic uncertainties, significantly enhancing motion accuracy in confined spaces. By bridging medical imaging and advanced robotics, Dr. Song’s research continues to push the boundaries of precision automation, offering practical solutions for both surgical and industrial applications.
Research Focus
Key Achievements
Top Papers
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