Ugonna Ohiri

Papers

Total Citations

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About

Ugonna Ohiri is a pioneering researcher in interactive robotics and multisensory perception, with a focus on enabling robots to recognize and manipulate objects through tactile and auditory feedback. Their most-cited work, "Interactive object recognition using proprioceptive and auditory feedback" (2011, 63 citations), introduces a novel method where robots perform exploratory behaviors—such as lifting, shaking, dropping, and crushing—to observe changes in proprioceptive and auditory signals. This approach allows robots to identify household objects without relying solely on vision, advancing the field of active perception. Ohiri’s contributions have significant implications for assistive robotics and autonomous systems, particularly in environments where visual cues are limited. By integrating multiple sensory modalities, their research bridges the gap between robotic exploration and real-world object recognition, inspiring further work in sensorimotor learning. With a citation count reflecting growing interest in their methods, Ohiri continues to shape how robots interact with and understand their physical surroundings, making their work essential for students and researchers in robotics, artificial intelligence, and human-robot interaction.