Papers
3
Total Citations
33
H-Index
3
About
Chao Song is a researcher whose work sits at the intersection of robotics, autonomous navigation, and medical intervention. His primary research areas include human-robot interaction, path planning under uncertainty, and surgical robotics. Song’s most impactful contribution is his 2018 paper on robot navigation, which integrates human trajectory prediction with multiple travel modes to enable safe and socially compliant movement in crowded environments—a foundational challenge in mobile robotics, evidenced by its 22 citations. He has also advanced robotic manipulation through a novel virtual tactile POMDP-based path planning approach for object localization and grasping (2024, 7 citations), addressing perception and decision-making under partial observability. In the medical domain, Song contributed to a pioneering study on robot-assisted laparoscopy combined with thoracoscopy for treating hepatocellular carcinoma with inferior vena cava tumor thrombus (2023, 4 citations), demonstrating the translational potential of robotic systems in complex surgeries. His work bridges theoretical planning algorithms with real-world applications, from dynamic pedestrian spaces to delicate operating rooms, marking him as a versatile researcher shaping both autonomous and assistive robotics.
Research Focus
Key Achievements
Top Papers
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