Max Robotics — Global Service Robot Directory + US Certification

About

Giulio Schiavi is a leading researcher at the intersection of robotics, embodied AI, and large-scale machine learning. His work is centered on enabling robots to generalize across diverse tasks and environments, with a particular focus on learning from broad, multi-embodiment datasets. Schiavi’s most impactful contribution is his pivotal role in the **Open X-Embodiment** collaboration, which produced the RT-X models—a landmark effort that consolidated robotic learning datasets and demonstrated that large, high-capacity models can transfer skills across different robot platforms, much like pretrained models in NLP and computer vision. This work, cited over 220 times across its two versions, has become a foundational resource for the field, driving a paradigm shift toward generalist robotic policies. Additionally, Schiavi has advanced interactive manipulation by introducing **agent-aware affordances** for closed-loop control of articulated objects, integrating manipulation priors with whole-body motion planning. His research not only pushes the boundaries of robot generalization but also provides practical pipelines for real-world interaction, making him a key figure in the movement toward scalable, data-driven robotics.