Samira Badrloo

Southwest Jiaotong University, PNPE Company (Iran)

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About

Samira Badrloo is a rising researcher in autonomous navigation and computer vision, whose work is shaping how unmanned vehicles perceive and interact with their environment. Her primary research focuses on obstacle detection for mobile robots, with a particular emphasis on image-based methods that enable safe navigation for Unmanned Surface Vehicles (USVs), Unmanned Aerial Vehicles (UAVs), and Micro Aerial Vehicles (MAVs). Badrloo’s most influential contribution is her comprehensive review, "Image-Based Obstacle Detection Methods for the Safe Navigation of Unmanned Vehicles: A Review" (2022), which has garnered 89 citations—a testament to its value as a foundational resource for researchers and engineers in the field. This work synthesizes decades of techniques, providing a critical roadmap for advancing autonomous systems. More recently, she has pushed the boundaries of real-time performance with "Fast and accurate obstacle detection based on stereo vision and deep learning" (2025), addressing the pressing need for speed and precision in dynamic environments. By bridging traditional stereo vision with modern deep learning, Badrloo is pioneering solutions that bring us closer to fully autonomous, collision-free navigation. Her growing citation impact and innovative approach mark her as a key contributor to the next generation of intelligent robotics.