Papers
6
Total Citations
18
H-Index
3
About
Songjie Xiao is a pioneering researcher at the intersection of medical robotics, human-robot interaction, and engineering education. His primary research focuses on developing intelligent control systems for ultrasound-guided robot-assisted procedures, where he has made significant contributions to variable impedance and admittance control strategies that optimize image quality while ensuring patient safety during remote scanning. His work on virtual potential field-based motion planning has advanced kinesthetically guided teleoperation for human-robot collaboration, enabling more intuitive and safer physical interactions. With over 18 citations across his most influential publications, Xiao's impact is particularly notable in his 2021 paper on visual optimization of ultrasound-guided procedures, which addresses the critical challenge of surgeon-dependent image quality. He has also pioneered innovative pedagogical approaches, introducing experiential active learning with immersive technology to make robotics education more accessible to engineering students. His recent work on large-scale digital twin parallelism for robotic arm trajectory planning demonstrates his commitment to pushing computational boundaries in robotics. Xiao's research portfolio, spanning compliant control for shape displays to safety-prioritized optimal search algorithms, showcases his versatility in solving real-world challenges across medical, industrial, and educational domains.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6