P. Bonnefoy

Papers

Total Citations

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About

P. Bonnefoy has made pioneering contributions to the field of mobile robotics, with a particular focus on sensor-based perception and intelligent obstacle recognition. Their research centers on the integration of ultrasonic sensing technologies with neural network architectures to enable robots to interpret and navigate complex environments. Bonnefoy’s most cited work, "Classification of sonar data for a mobile robot using neural networks" (2002, 8 citations), introduces an innovative ultrasonic sensor design paired with a neural classification algorithm. This system allows a mobile robot to accurately identify geometric obstacles, a fundamental challenge in autonomous navigation. By combining an array of ultrasonic transducers with machine learning, Bonnefoy advanced the practical application of sonar data beyond simple distance measurement, enabling more nuanced environmental understanding. Though their citation count is modest, the work represents a focused and early effort in bridging sensor hardware and AI-driven perception, laying groundwork for later developments in robotic sensing. Bonnefoy’s research is particularly valuable for students and engineers interested in low-cost, robust sensor solutions for mobile robots operating in unstructured settings.