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

By Yang Liu, Weixing Chen, Yongjie Bai, Jing-Hua Luo, Xinshuai Song, Kaixuan Jiang, Zhida Li, Ganlong Zhao, Junyi Lin, Guanbin Li and 2 more. IEEE/ASME transactions on mechatronics, 2024

318 citations recorded by the source corpus.

Embodied artificial intelligence (Embodied AI) is crucial for achieving artificial general intelligence (AGI) and serves as a foundation for various applications (e.g., intelligent mechatronics systems, smart manufacturing) that bridge cyberspace and the physical world. Recently, the emergence of multimodal large models (MLMs) and World models (WMs) have attracted significant attention due to their remarkable perception, interaction, and reasoning capabilities, making them a promising architecture for embodied agents. In this survey, we give a comprehensive exploration of the latest advancements in Embodied AI. Our analysis firstly navigates through the forefront of representative works of embodied robots and simulators, to fully understand the research focuses and their limitations. Then, we analyze four main research targets: 1) embodied perception, 2) embodied interaction, 3) embodied agent, and 4) sim-to-real adaptation, covering state-of-the-art methods, essential paradigms, and comprehensive datasets. In addition, we explore the complexities of MLMs in virtual and real embodied agents, highlighting their significance in facilitating interactions in digital and physical environments. Finally, we summarize the challenges and limitations of embodied AI and discuss potential future directions. We hope this survey will serve as a foundational reference for the research community.

Subfields: Architecture, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/7080139d78e718b0efe91cf1bbfe17f288100596