Yuxiang Gao

Papers

Total Citations

162

H-Index

About

Yuxiang Gao is a robotics researcher whose work sits at the intersection of human-robot interaction, socially-aware navigation, and end-user robot programming. His research addresses one of the most pressing challenges in modern robotics: enabling mobile robots to operate safely and naturally alongside people in everyday shared environments. Gao's most impactful contribution, "Evaluation of Socially-Aware Robot Navigation" (2022, 98 citations), has become a foundational reference in the field, offering a much-needed framework for assessing how robots navigate among people in socially acceptable ways. Complementing this, his work on group-aware navigation — spanning both a 2020 conference paper and a 2022 policy-learning approach (19 citations) — pushes beyond treating pedestrians as isolated individuals, instead modeling the social dynamics of human groups to produce more realistic and considerate robot behavior. Beyond navigation, Gao has contributed to democratizing robot programming through PATI (2019, 35 citations), a system designed to help non-expert users retask assistive robots. His more recent work on human-robot partnerships through task training further reflects his commitment to making robots genuinely useful collaborators in daily life. Across his portfolio, Gao's research consistently bridges technical rigor with real-world human needs.