M. A. Amiri Atashgah
Papers
12
Total Citations
85
H-Index
6
About
M. A. Amiri Atashgah is a prominent researcher specializing in aerial robotics, autonomous navigation, and intelligent control systems for unmanned aerial vehicles (UAVs). With a career spanning over a decade, their work has made substantial contributions to some of the most challenging problems in drone technology, including autonomous navigation in GPS-denied environments, robust control strategies, and AI-driven mission planning. Their most impactful contribution to date is a 2024 study on energy-aware hierarchical reinforcement learning for search and rescue drones in unknown environments, which has already garnered 23 citations, reflecting the growing urgency of autonomous disaster-response robotics. Earlier foundational work explored optical flow-based navigation inspired by biological systems, robust H∞ control for quadrotor path tracking, and augmented inertial navigation using motion jerk and jounce, each advancing UAV reliability in real-world conditions. Atashgah has also made notable strides in cooperative multi-robot navigation, developing model-based frameworks that maintain positioning accuracy when satellite signals are unavailable — a critical capability for emergency operations. Their research on SLAM integration, urban trajectory optimization, and uncertainty propagation in cooperative systems further demonstrates a comprehensive and systems-level approach to aerial autonomy. Collectively, their body of work provides essential building blocks for next-generation autonomous drone systems.
Research Focus
Key Achievements
Top Papers
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- 4Model-Based Cooperative Navigation for a Group of Flying Robots8 citations · 2022
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- 8Integration of image de-blurring in an aerial Mono-SLAM5 citations · 2013
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