Research on Robot Systems for Embodied Intelligence Applications
A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Network Services and Applications".
Deadline for manuscript submissions: 31 January 2027 | Viewed by 687
Special Issue Editors
Interests: big data analysis and computer vision techniques; big data analysis and natural language processing technology; intelligent robot operating system
Special Issues, Collections and Topics in MDPI journals
Interests: image recognition and natural language processing; distributed algorithms in artificial intelligence; federated learning; embodied intelligence
Special Issue Information
Dear Colleagues,
This Special Issue, “Research on Robot Systems for Embodied Intelligence Applications”, focuses on recent advances in robotic systems that realize embodied intelligence through closed-loop interactions with physical environments. Embodied intelligence emphasizes that intelligent behavior emerges from the tight coupling of perception, decision making, learning, and action, where sensory feedback, actuator responses, and adaptive control jointly support autonomous reasoning and task execution in real-world settings.
This Special Issue aims to provide a forum for original research on theories, models, algorithms, system architectures, and experimental platforms that advance robot systems for embodied intelligence applications. We welcome contributions addressing key challenges in multimodal perception, sensor fusion, sensorimotor coordination, embodied learning, reinforcement learning, world modeling, human–robot interaction, distributed and multi-robot collaboration, intelligent control, and safe real-world deployment. Particular interest will be given to studies that integrate sensors, actuators, communication, and computation to enable robust and adaptive interaction in complex and dynamic environments.
Applications of interest include service robotics, industrial automation, healthcare and assistive robotics, autonomous vehicles, smart manufacturing, and other sensor-rich embodied AI scenarios. By bringing together interdisciplinary work from robotics, artificial intelligence, sensor and actuator networks, control, and cognitive systems, this Special Issue seeks to promote both theoretical advances in and practical implementations of embodied intelligent robot systems.
Prof. Dr. Jianwei Niu
Dr. Xuefeng Liu
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Sensor and Actuator Networks is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- embodied intelligence
- robot systems
- autonomous robots
- multimodal perception
- sensor fusion
- sensorimotor coordination
- human–robot interaction
- reinforcement learning
- intelligent control
- multi-robot systems
- sensor and actuator networks
- embodied AI
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