Muhammad Azriel Rizqifadiilah
Papers
1
Total Citations
2
H-Index
1
About
Muhammad Azriel Rizqifadiilah is a robotics researcher specializing in autonomous navigation, environmental perception, and mobile robot localization. His work centers on integrating sensor fusion and real-time mapping techniques to enhance the situational awareness of non-holonomic differential drive robots. In his most cited paper, "Environmental localization and detection using 2D LIDAR on a non-holonomic differential mobile robot" (2023, 2 citations), he introduces a novel methodology that combines SLAM-based real-time localization with Euclidean Clustering for multi-object detection. This contribution addresses critical challenges in low-cost, 2D LIDAR-based systems, enabling robots to accurately perceive and navigate complex indoor environments. Rizqifadiilah’s research is particularly significant for applications in warehouse automation, service robotics, and assistive mobility platforms, where reliable object detection and self-localization are essential. His work demonstrates a practical, computationally efficient approach that balances accuracy with real-time performance, making it accessible for implementation on resource-constrained robotic platforms. As an emerging voice in field robotics, Rizqifadiilah continues to advance the integration of perception and control in autonomous systems, with potential implications for safer and more adaptive human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1