Resources

Chef Robotics uses NVIDIA Isaac Sim, Omniverse libraries, and cuMotion to accelerate development and deployment of its food-manipulation robots while maintaining reliability in production.

This blog explains how Chef robots support worker safety with collaborative robot arms, built-in safeguards, and ergonomic features that reduce repetitive tasks and physical strain on meal assembly lines.

Generalizability matters, but it differs between generalizing within a domain and generalizing across unrelated tasks. This blog explains why industrial robots need domain generalizability to handle the tasks and variations within their industry while meeting the speed, quality, and reliability requirements that make automation worthwhile.

Given a pan of food and a candidate pick, our Food World Model (FWM) predicts how much of an ingredient our robot will pick and what surface it will leave behind in the ingredient pan. This blog describes an initial run of the FWM based on production picks across nine food ingredients. It includes an interactive visualizer for readers to explore.

A new survey paper by Chef Robotics Senior Staff AI Research Scientist Inkyu Sa maps the relatively new field of world models and world-action models and evaluates which modeling approaches are best suited for robotics, autonomous driving, reinforcement learning, games, and general-purpose simulation.

A new survey paper by Chef Robotics Senior Staff AI Research Scientist Inkyu Sa examines the rapidly evolving field through one of robotics' hardest challenges: bimanual manipulation, or coordinating two arms to complete tasks such as folding fabric, assembling objects, and handling deformable materials.