  We present a retrospective on the state of Embodied AI research. Our analysis
focuses on 13 challenges presented at the Embodied AI Workshop at CVPR. These
challenges are grouped into three themes: (1) visual navigation, (2)
rearrangement, and (3) embodied vision-and-language. We discuss the dominant
datasets within each theme, evaluation metrics for the challenges, and the
performance of state-of-the-art models. We highlight commonalities between top
approaches to the challenges and identify potential future directions for
Embodied AI research.
