Rusdhianto Effendi
Sepuluh Nopember Institute of Technology, Petra Christian University
Papers
5
Total Citations
36
H-Index
3
About
Rusdhianto Effendi is a leading researcher in autonomous mobile robotics, specializing in intelligent navigation systems for complex, cluttered environments. His work centers on the innovative hybridization of fuzzy logic and reinforcement learning, particularly through Fuzzy Q-Learning, to enable robots to navigate without predefined maps. Effendi’s most influential contribution is the design of a reinforcement point and fuzzy input system that minimizes state space in Q-learning, allowing mobile robots to effectively avoid obstacles—a paper that has garnered 15 citations. He further advanced the field by integrating Fuzzy Q-Learning with behavior-based control architectures, creating robust navigation systems for both wheeled and legged robots, including hexapods and a biologically-inspired five-legged robot modeled after a sea star. His research on modified fuzzy behavior coordination addresses critical limitations like slow movement and trap avoidance, enhancing robot efficiency. With a focus on practical applications, Effendi’s work has significantly impacted autonomous navigation, offering scalable solutions for real-world challenges in robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Hybridization of fuzzy Q-learning and behavior-based control for autonomous mobile robot navigation in cluttered environment11 citations · 2009
- 3Perancangan Sistem Navigasi Otonom pada Behavior Based Hexapod Robot4 citations · 2010
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- 5