Evaluating Embodied AI Performance

Design a comprehensive framework for evaluating embodied AI systems that operate in real-world environments. Include a taxonomy of tasks (manipulation, navigation, social interaction), performance metrics (efficiency, safety, robustness, generalization), testbed design across diverse environments, and methods for conducting fair, comparable evaluations. Propose governance and ethics considerations, data reporting standards, and a phased roadmap to advance from lab prototypes to field-ready deployments.