Muhammad Hafizd Ibnu Hajar
Papers
7
Total Citations
30
H-Index
3
About
Muhammad Hafizd Ibnu Hajar is a robotics and control systems researcher whose work centers on intelligent control algorithms, mobile robot navigation, and autonomous systems optimization. His research consistently explores the fusion of classical control theory with bio-inspired and soft computing techniques to solve real-world robotics challenges. Hajar is perhaps best recognized for his contributions to wall-following robot (WFR) control, a foundational problem in mobile robotics. His most-cited work (10 citations) demonstrated how integrating Fuzzy Logic Controllers with Genetic Algorithms significantly improves robot motion smoothness and trajectory accuracy. This line of inquiry expanded across multiple studies, incorporating Particle Swarm Optimization, Ant Colony Algorithms, and Artificial Bee Colony methods to fine-tune PID and FLC parameters — work that has collectively garnered over 20 citations. Beyond mobile navigation, Hajar has tackled robot localization using adaptive Smooth Variable Structure Filters and addressed precision motion planning for 6-DoF robotic arms through inverse kinematics frameworks. His earlier IoT-based firefighting robot project further illustrates his commitment to practical, application-driven robotics. Spanning foundational robot control to advanced estimation and manipulation, Hajar's growing body of work marks him as an emerging contributor to intelligent robotics research with meaningful impact across autonomous systems design.
Research Focus
Key Achievements
Top Papers
- 1ENHANCING THE PERFORMANCE OF THE WALL-FOLLOWING ROBOT BASED ON FLC-GA10 citations · 2020
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- 5Robot Pemadam Kebakaran Berbasis Wemos3 citations · 2019
- 6The ACA-based PID Controller for Enhancing a Wheeled-Mobile Robot2 citations · 2020
- 7AN FLC-PSO ALGORITHM-CONTROLLED MOBILE ROBOT2 citations · 2020