IEEE Transactions on Cognitive and Developmental Systems

Special issue on “Embodied Intelligence for Wearable Robotics”

Due to the potential advantages of human augmentation, intelligent control, and enhanced user experiences, wearable robotics have captured considerable attention. Despite the broad application prospects of wearable robotics, the development of wearable robotics has been hampered by several challenges related to deficiencies in intelligence and adaptability. These challenges can be addressed through the integration of advanced artificial intelligence techniques, such as Embodiment AI, which provides wearable robots with more advanced functionality and intelligent decision-making capabilities. By employing machine learning and deep learning techniques, wearable robots can learn from vast amounts of data, recognize patterns, and achieve autonomous decision-making and action, which can significantly improve their adaptability and user-friendliness. Thus, exploring and optimizing these areas, particularly intelligent control algorithms, adaptive ability, and human-robot interaction, along with embodied intelligence, holds great promise for enhancing the effectiveness, efficiency, and user-friendliness of wearable robotics, thereby promoting their widespread adoption.

This special issue is intended to expedite publication of novel and significant research results, technology and/or conceptual breakthrough of emerging topics of Embodied Intelligence for Wearable Robotics. We invite submission of high-quality papers as related to recent advances in such emerging topics, including but are not limited to the following:

• Embodied intelligent control for wearable robotics;
• Applications of wearable robotics in healthcare;
• Embodied cognition and its applications in wearable robotics;
• Advances in machine learning and deep learning for wearable robotics;
• Human-robot interaction in wearable robotics;
• Enhancement of adaptive ability in wearable robotics through AI;
• Embodied Intelligence with sensing and perception in wearable robotic;
• Embodied intelligence inspired learning solution for wearable robotics;
• Developing personalized models for wearable robotics using AI;
• Human-centered design for AI in wearable robotics;

Submission Guidelines

Important Dates

Guest Editors

Hang Su, Silesian University of Technology, Poland, Email: hang.su@ieee.org

Haisheng Xia, Univ. of Science and Tech. of China, China, Email: hsxia@ustc.edu.cn

Guang Chen, Tongji University, China, Email: guangchen@tongji.edu.cn

Hao Su, North Carolina State University, USA, Email: hsu4@ncsu.edu

M. A. LARIBI, Université de Poitiers, France, Email: med.amine.laribi@univ-poitiers.fr