Papers
6
Total Citations
31
H-Index
3
About
Luhur Bayuaji is a robotics researcher whose work centers on autonomous navigation, control systems, and fault detection for mobile and aerial robots. His major contributions lie in advancing 3D scene reconstruction for robot navigation using stereo vision, where he demonstrated how accurate camera calibration and disparity mapping can generate precise 3D coordinates—a foundational technique for autonomous movement. Bayuaji has also made significant strides in optimizing PID controllers for wheeled mobile robots, comparing bio-inspired algorithms like the Bat Algorithm and Particle Swarm Optimization to achieve superior gain tuning. His research extends to fault detection and isolation (FDI) in complex nonlinear systems, using a two-wheel robot as a testbed to monitor and pinpoint system faults. With over 30 citations across his most-cited papers, his work on 3D reconstruction (12 citations) and PID optimization (7 citations) has had notable impact. More recently, he has explored micro aerial vehicle (MAV) design and control using Webots simulation, addressing applications from surveillance to disaster response. Bayuaji’s blend of theoretical modeling and practical implementation makes his research valuable for students and engineers seeking robust, real-world robotic solutions.
Research Focus
Key Achievements
Top Papers
- 1Study on 3D scene reconstruction in robot navigation using stereo vision12 citations · 2016
- 2
- 3Fault detection and isolation for complex system4 citations · 2017
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