Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI

Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI

26 Aug 2024 | Yang Liu, Weixing Chen, Yongjie Bai, Xiaodan Liang, Guanbin Li, Wen Gao, Fellow, IEEE, Liang Lin, Fellow, IEEE
This paper provides a comprehensive survey of Embodied AI, focusing on the alignment of cyber space with the physical world. It highlights the importance of Embodied AI in achieving Artificial General Intelligence (AGI) and its applications in various fields. The survey covers recent advancements in Multi-modal Large Models (MLMs) and World Models (WMs), which have significantly enhanced the perception, interaction, and reasoning capabilities of embodied agents. The paper analyzes four main research areas: embodied perception, embodied interaction, embodied agents, and sim-to-real adaptation, discussing state-of-the-art methods, paradigms, and datasets. It also explores the complexities of MLMs in virtual and real embodied agents and their significance in facilitating interactions in dynamic environments. Finally, the paper identifies challenges and future directions in Embodied AI, aiming to serve as a foundational reference for researchers and inspire continued innovation. The survey includes detailed sections on different types of embodied robots, simulators, and specific tasks, providing a broad overview of the current landscape and future potential of Embodied AI.This paper provides a comprehensive survey of Embodied AI, focusing on the alignment of cyber space with the physical world. It highlights the importance of Embodied AI in achieving Artificial General Intelligence (AGI) and its applications in various fields. The survey covers recent advancements in Multi-modal Large Models (MLMs) and World Models (WMs), which have significantly enhanced the perception, interaction, and reasoning capabilities of embodied agents. The paper analyzes four main research areas: embodied perception, embodied interaction, embodied agents, and sim-to-real adaptation, discussing state-of-the-art methods, paradigms, and datasets. It also explores the complexities of MLMs in virtual and real embodied agents and their significance in facilitating interactions in dynamic environments. Finally, the paper identifies challenges and future directions in Embodied AI, aiming to serve as a foundational reference for researchers and inspire continued innovation. The survey includes detailed sections on different types of embodied robots, simulators, and specific tasks, providing a broad overview of the current landscape and future potential of Embodied AI.
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[slides and audio] Aligning Cyber Space with Physical World%3A A Comprehensive Survey on Embodied AI