Sepehr Samavi
Papers
2
Total Citations
11
H-Index
1
About
Sepehr Samavi is a rising researcher at the forefront of safe and interactive robot navigation in crowded human environments. His work focuses on the critical challenge of enabling autonomous robots to move seamlessly through crowds by integrating human motion prediction directly into robot control systems. Samavi’s major contribution is the development of the SICNav framework (Safe and Interactive Crowd Navigation), which uses model predictive control and bilevel optimization to couple human trajectory prediction with robot planning, preventing the robot from getting stuck by accounting for bidirectional human-robot interaction. His most cited paper, “SICNav” (2024), has already garnered 10 citations for this novel approach. Building on this, his 2025 work “SICNav-Diffusion” advances the field by incorporating diffusion-based trajectory prediction models, addressing the challenge of integrating stochastic human forecasts into deterministic robot controllers. Though early in his career, Samavi’s research is gaining traction for its practical, safety-critical approach to human-robot interaction, promising more fluent and collision-free navigation in real-world crowded settings.
Research Focus
Key Achievements
Top Papers
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