Oussama Yaakoubi

Centre National de la Recherche Scientifique

Papers

Total Citations

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About

Oussama Yaakoubi is an emerging researcher specializing in robotic perception, affordance learning, and human-robot interaction. His work addresses one of the fundamental challenges in autonomous robotics: enabling robots to meaningfully understand and interact with open, unstructured environments. Rather than relying on pre-programmed visual scene analysis — which works well only in controlled settings — Yaakoubi's research explores how robots can dynamically learn to map affordances through direct interaction with their surroundings, a paradigm known as interactive perception. His most notable contribution, "Building an Affordances Map with Interactive Perception," has been developed across multiple iterations (2019 and 2022), reflecting a sustained and evolving research commitment to this problem. The 2022 version has garnered 8 citations, demonstrating growing recognition within the robotics and artificial intelligence communities. This body of work is particularly significant because it bridges perception and action, allowing robots to discover what objects afford — what actions they enable — through experience rather than explicit programming. While still early in his research career, Yaakoubi's focus on adaptive, learning-driven robotic systems positions him as a promising contributor to the broader field of autonomous and cognitive robotics, with implications for service robots, manufacturing, and assistive technologies.