Hadi Seyedarabi

Papers

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About

Hadi Seyedarabi’s research focuses on advancing autonomous navigation and localization systems for mobile robots, with a particular emphasis on low-cost, biologically inspired solutions. His work addresses critical challenges in inertial navigation and simultaneous localization and mapping (SLAM), aiming to make these technologies more accessible and reliable for real-world applications. One of his key contributions is a correcting approach for gyroscope-free inertial navigation, which leverages topological maps to mitigate accumulated error and noise sensitivity—common issues with affordable accelerometer-based systems. This work, cited 6 times, offers a practical alternative to expensive gyroscopes for low-cost robotic missions. Seyedarabi also developed a hybrid navigation method that integrates GPS data with SIFT-based place recognition within a biologically inspired RatSLAM framework. By improving place recognition in indoor environments, this approach, cited 4 times, enhances the robustness of SLAM systems modeled after the mammalian hippocampus. His research demonstrates a commitment to bridging the gap between biological principles and engineering solutions, contributing to more efficient and cost-effective autonomous navigation. Seyedarabi’s work is particularly relevant for students and researchers interested in sensor fusion, bio-inspired robotics, and practical SLAM implementations.