Papers
1
Total Citations
2
H-Index
1
About
Jiamin Shi is a robotics researcher whose work addresses the critical challenge of safe and efficient robot navigation in crowded, human-filled environments. Her research centers on integrating advanced perception, graph-based modeling, and predictive control to enable autonomous systems to operate seamlessly alongside people. Shi’s most-cited paper, “Robot Crowd Navigation Based on Spatio-Temporal Interaction Graphs and Danger Zones” (2023), introduces a novel framework that moves beyond traditional assumptions of full observability. By modeling dynamic spatio-temporal interactions between agents and defining danger zones, her approach allows robots to navigate partially observable, real-world crowds with enhanced safety and foresight. This work has already garnered attention for its practical relevance, earning 2 citations in a short time. Shi’s contributions are particularly notable for bridging the gap between simulation-based research and real-world deployment, addressing the limitations of prior methods that rely on known pedestrian dynamics. Her innovative use of graph-based reasoning to capture complex social interactions positions her as a rising figure in mobile robotics, with implications for service robots, autonomous delivery, and human-robot collaboration in public spaces.
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Top Papers
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