Fetoh H. Ketafa
Papers
2
Total Citations
7
H-Index
2
About
Fetoh H. Ketafa is an emerging researcher specializing in autonomous mobile robotics, with a particular focus on intelligent path planning and bio-inspired optimization algorithms. Their work addresses one of the most fundamental challenges in robotics — enabling autonomous mobile robots to navigate complex environments safely and efficiently while avoiding static obstacles. Ketafa's most notable contributions include the development and application of novel optimization frameworks for robot path planning. In 2022, they introduced the Red Fox Optimization (RFO) algorithm, a bio-inspired approach designed to generate collision-free paths in known static environments. Building on this foundation, their 2024 work presented an innovative hybrid RFO-GWO (Red Fox Optimization–Grey Wolf Optimizer) algorithm, combining two powerful metaheuristic techniques within a three-stage multi-objective path-planning methodology, reflecting a maturing and increasingly sophisticated research trajectory. Although Ketafa's publication record is still growing, their papers have already attracted citations within the robotics and computational intelligence communities, accumulating 7 combined citations across just two years. This early impact signals promising potential in a competitive field where efficient autonomous navigation is critical to applications ranging from industrial automation to search-and-rescue robotics. Researchers interested in swarm intelligence and autonomous systems would find Ketafa's work a valuable reference point.
Research Focus
Key Achievements
Top Papers
- 1
- 2