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About

Alessio Xompero is a computer vision and robotics researcher whose work sits at the intersection of perception, multi-modal sensing, and human-robot interaction. He is perhaps best known for his pioneering contributions to the CORSMAL project, which addresses one of robotics' most nuanced challenges: enabling robots to safely and accurately receive objects handed to them by humans. His highly cited 2020 benchmark paper (41 citations) introduced a rigorous framework for estimating the 3D pose, dimensions, and physical properties of previously unseen containers in real time — a critical capability for safe robotic grasping. This work was extended through the CORSMAL Benchmark (2022), which targets contactless weight and content estimation despite the visual complexities of transparent and opaque materials. Beyond human-robot handovers, Xompero has contributed to multi-person tracking using variational Bayesian methods (38 citations), audio-visual object classification for collaborative robotics, and robust binary descriptors for multi-view matching under challenging viewpoint changes. His involvement in the 2024 IEEE ICRA Robotic Grasping and Manipulation Competition further reflects his commitment to advancing reproducible, community-driven robotics research. Across his body of work, Xompero demonstrates a consistent drive to bridge perception and physical interaction, making robots more capable collaborators in real-world human environments.