Masoud Fetanat
Papers
1
Total Citations
28
H-Index
1
About
Masoud Fetanat is a researcher whose work lies at the intersection of robotics, optimization, and intelligent systems. His primary research areas include mobile robot path planning, evolutionary algorithms, and dynamic system optimization. Fetanat’s most-cited paper, “Optimization of dynamic mobile robot path planning based on evolutionary methods” (2015, 28 citations), makes a significant contribution by addressing the challenge of navigating robots through environments with moving obstacles. He introduces evolutionary techniques to generate optimal, smooth, and safe paths from a starting point to a target, balancing efficiency with real-time adaptability. This work has been foundational for researchers developing autonomous navigation systems in unpredictable settings. Fetanat’s approach demonstrates a practical fusion of computational intelligence and robotics, offering solutions that prioritize both feasibility and performance. His research continues to influence the design of smarter, more responsive mobile robots, and his contributions are recognized by peers working in path planning and optimization. For students and researchers, Fetanat’s work exemplifies how evolutionary methods can solve complex, real-world robotic challenges.
Research Focus
Key Achievements
Top Papers
- 1