M. Hossein Mirabdollah

Papers

Total Citations

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About

M. Hossein Mirabdollah is a researcher specializing in mobile robotics localization and monocular SLAM (Simultaneous Localization and Mapping), with a focus on probabilistic estimation techniques. His work addresses fundamental challenges in robot perception using limited sensory data, particularly bearing-only measurements common in monocular vision systems. In his most cited work, "Bearing only mobile robots' localization: Observability and formulation using SIS particle filters" (2011, 4 citations), he rigorously analyzed the observability conditions for robot localization using only angular measurements and formulated a solution using Sequential Importance Sampling particle filters. This contribution is critical for robots equipped with a single camera, where depth information is unavailable. Expanding on this foundation, his 2012 paper "Monocular SLAM: Using trapezoids to model landmark uncertainties" (3 citations) introduced an innovative approach to represent landmark uncertainty using trapezoidal shapes attached to particles, specifically designed for scenarios with negligible measurement noise. This method offers a computationally efficient alternative for consumer-grade cameras on mobile platforms. Though his citation counts are modest, Mirabdollah's work provides valuable theoretical insights into observability and uncertainty modeling in monocular SLAM, contributing to the broader field of vision-based robot navigation.