Papers
3
Total Citations
28
H-Index
2
About
Javad Amirian investigates the intersection of robotics, crowd dynamics, and human-robot interaction, with a focus on how autonomous systems perceive and behave within densely populated environments. His work bridges the gap between traditional human-robot interaction (HRI) and the emerging field of crowd-robot interaction (CRI), exploring how robots influence pedestrian movement and social dynamics. In his highly cited 2021 paper, "From HRI to CRI," Amirian conducted controlled experiments demonstrating that a robot's presence measurably alters crowd motion—a finding with 21 citations that underscores its foundational importance. He further advanced socially-compliant robot navigation through "Legibot," a 2024 framework that enables service robots to generate legible, intention-revealing motions using cost-based local planners, making robot behavior more predictable and trustworthy for human bystanders. Addressing a critical sensing challenge, his work on imputing occluded crowd structures from limited robot perception tackles the real-world problem of navigating blind spots, enabling robots to infer human occupancy beyond their immediate sensor range. Amirian’s contributions are shaping how robots understand and integrate into human crowds, paving the way for safer, more intuitive autonomous navigation in public spaces.
Research Focus
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Top Papers
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