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Fan et al. Intell. Robot. 2025, 5, 859-63 Intelligence & Robotics
DOI: 10.20517/ir.2025.44

Editorial Open Access

Toward the next frontier of embodied AI

Rui Fan 1 , Mingjian Sun 2,3,4,5,6 , George Giakos 7
1
Department of Control Science & Engineering, Tongji University, Shanghai 201804, China.
2
Harbin Institute of Technology (Weihai) Qingdao Innovation and Development Base, Qingdao 266109, Shandong, China.
3
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China.
4
Harbin Institute of Technology, Weihai, Weihai 264200, Shandong, China.
5
Harbin Institute of Technology Suzhou Research Institute, Suzhou 215000, Jiangsu, China.
6
Shandong Laboratory of Advanced Biomaterials and Medical Devices in Weihai, Weihai 264209, Shandong, China.
7
Department of Electrical & Computer Engineering, Manhattan University, University Park, PA 16802, USA.
Correspondence to: Prof. Rui Fan, Department of Control Science & Engineering, Tongji University, Shanghai 201804, China. E-
mail: rui.fan@ieee.org
How to cite this article: Fan, R.; Sun, M.; Giakos, G. Toward the next frontier of embodied AI. Intell. Robot. 2025, 5, 859-63.
https://dx.doi.org/10.20517/ir.2025.44
Received: 4 Nov 2025 Accepted: 17 Nov 2025 Published: 2 Dec 2025
Academic Editor: Simon Yang Copy Editor: Ting-Ting Hu Production Editor: Ting-Ting Hu

Abstract
Embodied artificial intelligence has emerged as a transformative paradigm, marking a fundamental shift in artificial
intelligence research toward systems that tightly couple perception, cognition, and action within real-world
environments. This editorial emphasizes the growing significance of embodied artificial intelligence, introduces the
key contributions presented in this Special Issue, and provides an overview of the current challenges and
prospective research directions shaping the future of the field.

Keywords: Robotics, artificial intelligence, embodied AI

1. INTRODUCTION
Recently, embodied artificial intelligence has emerged as a transformative paradigm in artificial intelligence
research, marking a significant shift toward systems that tightly couple perception, action, and interaction
within physical environments . Progress in this field is fueled by interdisciplinary insights and state-of-the-
[1]
art technologies, enabling the development of adaptive, autonomous agents that can navigate and learn
[2]
from complex, real-world scenarios . This evolution signals a new chapter in artificial intelligence, wherein
machines transcend passive observation to actively engage with their environments, exhibiting levels of
[3]
situational understanding that increasingly resemble human cognitive processes .

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0
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