APP Prasetyo
Papers
1
Total Citations
2
H-Index
1
About
APP Prasetyo is a researcher specializing in autonomous robotics and intelligent control systems, with a particular focus on maritime applications. His key research areas include autonomous surface vehicles (ASVs), obstacle avoidance algorithms, and fuzzy neural network systems. Prasetyo’s major contribution lies in the development of the Fuzzy Kohonen Network (FKN) method, which serves as the cognitive core for ASVs, enabling them to detect obstacles, measure distances, and navigate safely in dynamic environments. His seminal work, "Autonomous Surface Vehicle (ASV) Obstacle Avoidance Using Fuzzy Kohonen Network (FKN)" (2019), has garnered 2 citations, reflecting its foundational role in advancing autonomous maritime navigation. By integrating fuzzy logic with Kohonen neural networks, Prasetyo has created a robust decision-making framework that enhances the adaptability and reliability of robot boats. His research holds promise for applications in ocean exploration, environmental monitoring, and search-and-rescue operations. As a dedicated innovator, Prasetyo continues to push the boundaries of autonomous systems, making him a notable figure in the field of intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1