Akhmad Thalibar Rifqi
Papers
1
Total Citations
7
H-Index
1
About
Akhmad Thalibar Rifqi is a researcher whose work lies at the intersection of robotics, artificial intelligence, and healthcare technology. His primary research areas include autonomous navigation, human-robot interaction, and intelligent obstacle avoidance systems. Rifqi’s most notable contribution is the development of the Fuzzy Social Force Model, a novel framework that enables healthcare robots to navigate safely and naturally in human-populated environments. This approach, detailed in his 2021 paper cited 7 times, integrates fuzzy logic with social force theory to allow robots to anticipate and respond to human movement, ensuring smooth, obstacle-free trajectories. By leveraging sensors like Laser Range Finders, his work addresses the critical challenge of deploying robots in dynamic social settings, such as hospitals and care facilities. Rifqi’s research has practical implications for improving the autonomy and safety of service robots, making them more effective assistants in healthcare. His achievements highlight a commitment to bridging theoretical AI models with real-world robotic applications, offering a foundation for future innovations in socially-aware navigation systems.
Research Focus
Key Achievements
Top Papers
- 1