Koko Joni
Papers
4
Total Citations
35
H-Index
3
About
Koko Joni is an Indonesian robotics and artificial intelligence researcher whose work centers on autonomous mobile robot systems, intelligent control algorithms, and humanoid robot dynamics. His most influential contribution, a 2017 study garnering 22 citations, delivers a rigorous comparative analysis of backpropagation neural networks and fuzzy logic controllers applied to wall-following autonomous mobile robots — a foundational problem in mobile robotics navigation. This work highlighted the practical trade-offs between these AI methodologies in real-world robot control scenarios. Beyond navigation intelligence, Joni has made notable strides in vision-based obstacle avoidance, developing a camera-driven contour detection system that enables robots to not only avoid obstacles but also identify target locations — addressing a significant limitation of traditional sensor-based approaches. His research on line-follower robots explores advanced control strategies for handling complex track geometries, while his 2019 work on humanoid robot balance control investigates complementary filters optimized with PID controllers to achieve stable, harmonious movement. Collectively, Joni's research bridges theoretical AI techniques and practical robotic implementation, contributing meaningfully to the field of intelligent autonomous systems and establishing him as a productive voice in Indonesian robotics research.
Research Focus
Key Achievements
Top Papers
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