Franck Harroy

Papers

Total Citations

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About

Franck Harroy’s research lies at the intersection of robotics, sensor systems, and intelligent data classification, with a particular focus on enabling mobile robots to perceive and interpret their environments. His most-cited work, “Classification of sonar data for a mobile robot using neural networks” (2002, 8 citations), introduces a novel ultrasonic sensor architecture paired with a neural network-based classification algorithm. This system allows a mobile robot to recognize geometric obstacles by processing data from an array of ultrasonic transducers, demonstrating how machine learning can enhance low-cost sensing for autonomous navigation. Harroy’s contribution is notable for bridging hardware design and algorithmic intelligence, offering a practical solution to real-world robotic perception challenges. While his citation count reflects a focused, specialized impact, his work is foundational for researchers exploring sensor fusion and neural network applications in robotics. By integrating neural networks with sonar data, Harroy advanced the field’s understanding of how robots can interpret complex, noisy sensory inputs—a key step toward more autonomous and adaptable machines. His research remains relevant for students and engineers developing intelligent sensing systems for mobile platforms.