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A Survey of Embodied AI: From Simulators to Research Tasks
There has been an emerging paradigm shift from the era of "internet AI" to
"embodied AI", where AI algorithms and agents no longer learn from datasets of
images, videos or text curated primarily from the internet. Instead, they learn
through interactions with their environments from an egocentric perception
similar to humans. Consequently, there has been substantial growth in the
demand for embodied AI simulators to support various embodied AI research
tasks. This growing interest in embodied AI is beneficial to the greater
pursuit of Artificial General Intelligence (AGI), but there has not been a
contemporary and comprehensive survey of this field. This paper aims to provide
an encyclopedic survey for the field of embodied AI, from its simulators to its
research. By evaluating nine current embodied AI simulators with our proposed
seven features, this paper aims to understand the simulators in their provision
for use in embodied AI research and their limitations. Lastly, this paper
surveys the three main research tasks in embodied AI -- visual exploration,
visual navigation and embodied question answering (QA), covering the
state-of-the-art approaches, evaluation metrics and datasets. Finally, with the
new insights revealed through surveying the field, the paper will provide
suggestions for simulator-for-task selections and recommendations for the
future directions of the field.Comment: Under Review for IEEE TETC
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