Anahid Basiri

University College London, Qazvin Islamic Azad University

Papers

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About

Anahid Basiri is a leading researcher in indoor positioning, autonomous navigation, and sensor fusion, with a focus on enhancing robotic systems in challenging environments. Her major contributions center on improving the accuracy and reliability of robot localization where traditional GPS fails, such as indoor spaces with high noise, low sampling rates, and sudden environmental changes. In her highly cited work, "Particle Filter and Finite Impulse Response Filter Fusion and Hector SLAM to Improve the Performance of Robot Positioning" (18 citations), she pioneered a hybrid filter algorithm that integrates particle and finite impulse response filters with Hector SLAM, significantly boosting indoor position estimation robustness. She also advanced low-cost sensing solutions in "Improving Robot Navigation and Obstacle Avoidance using Kinect 2.0" (4 citations), demonstrating how the upgraded Kinect sensor can be repurposed for effective obstacle avoidance and navigation. Basiri’s work is notable for bridging theoretical sensor fusion with practical, affordable implementations, making autonomous navigation more accessible. Her research has direct implications for robotics, IoT, and smart environments, and she is recognized for pushing the boundaries of indoor positioning systems in real-world, noisy conditions.