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About

Amirreza Kosari is a leading researcher in intelligent robotics, specializing in autonomous navigation and path planning for both humanoid and flying robots operating in complex, unknown environments. His work addresses a critical gap in robotics: enabling machines to make real-time, optimal decisions without prior environmental knowledge. Kosari’s most influential contribution is his pioneering integration of fuzzy logic with Markov decision processes, as detailed in his highly cited 2016 paper (77 citations), which provides a robust framework for humanoid robot path planning under uncertainty. He further advanced the field by revising fuzzy artificial potential field methods (33 citations), making them viable for real-world, unstructured settings. For aerial systems, Kosari has developed innovative solutions for terrain following and collision avoidance, including neural-network-based optimal trajectory generation (18 citations) and a unified approach to conflict resolution using the Radau-pseudo spectral method. His work is foundational for the next generation of autonomous robots, from search-and-rescue humanoids to swarms of flying drones navigating mountainous terrain. With over 140 total citations, Kosari’s research continues to shape the future of intelligent, adaptive robotics.