Hocine Abdelhak Azzedine

Université Mustapha Stambouli de Mascara

Papers

Total Citations

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About

Hocine Abdelhak Azzedine is a robotics researcher advancing safe physical human–robot interaction through intelligent, sensorless collision detection. His work focuses on developing model-based algorithms that eliminate the need for additional external sensors, reducing cost and complexity while maintaining high safety standards. His most-cited paper, “Sensorless robot collision detection based on fuzzy momentum observer” (2024, 3 citations), introduces a novel fuzzy logic approach to momentum observation, enabling robots to reliably detect unintended collisions during collaborative tasks. By combining fuzzy inference with dynamic modeling, Azzedine’s method improves detection accuracy and responsiveness without compromising robot performance. This contribution is particularly significant for the growing field of collaborative robotics, where human safety is paramount. Azzedine’s research addresses a critical gap in human–robot interaction: achieving robust, real-time collision detection in a sensorless framework. His work has the potential to influence the design of safer, more affordable robotic systems for manufacturing, healthcare, and service applications. As a researcher committed to practical, scalable solutions, Azzedine is helping shape the future of human–robot collaboration.