Mostafa Yaghobi

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About

Mostafa Yaghobi is a robotics researcher whose work centers on autonomous navigation, localization, and motion control for both wheeled and bipedal robots. His contributions span the full pipeline of robotic autonomy, from low-level motion planning to high-level environmental perception. In his highly cited 2007 paper, "Designing A Football Team of Robots From Beginning to End," Yaghobi developed an intelligent controller for omni-directional robots, integrating path planning with path following for the MRL small-size league—a foundational piece for multi-robot coordination in dynamic environments. He advanced bipedal robotics with his 2012 work on particle filter-based localization for Nao robots, providing a probabilistic, real-time solution for reliable self-localization in indoor settings. Yaghobi also made significant strides in SLAM (Simultaneous Localization and Mapping) through two key 2009 papers. He proposed an adaptive line extraction algorithm using a modified split-and-merge method, achieving high accuracy and robustness against sensor noise, and a recursive line extraction algorithm from 2D laser scanners for efficient mobile robot navigation. With over 34 citations across his most prominent works, Yaghobi’s research has directly influenced practical implementations in robot soccer, service robotics, and autonomous mapping, demonstrating a consistent focus on bridging theoretical algorithms with real-world robotic performance.