D. Diep

Papers

Total Citations

H-Index

About

D. Diep is a researcher whose work sits at the intersection of robotics, sensor systems, and artificial intelligence. Their most cited paper, "Classification of sonar data for a mobile robot using neural networks" (2002, 8 citations), introduces an innovative ultrasonic sensor architecture paired with a neural network-based classification algorithm. This system enables a mobile robot to recognize geometric obstacles by processing sonar data from an array of ultrasonic transducers. While the citation count is modest, the work represents an early and practical application of neural networks to real-world robotic perception—a field that has since exploded in importance. Diep’s contribution lies in bridging hardware design with intelligent software, offering a cost-effective solution for obstacle recognition that could inform later advances in autonomous navigation. Their research demonstrates a thoughtful integration of sensing and learning, making it a valuable reference for students and engineers exploring sensor-based robotics.