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EDITORIAL article
Front. Neurorobot.
Volume 19 - 2025 | doi: 10.3389/fnbot.2025.1587137
This article is part of the Research Topic Neural Network Models in Autonomous Robotics View all 7 articles
Editorial: Neural Network Models in Autonomous Robotics
Provisionally accepted- 1 North China Electric Power University, Beijing, China
- 2 Fordham University, New York City, New York, United States
- 3 Dublin City University, Dublin, County Dublin, Ireland
The integration of neural network models in autonomous robotics represents a monumental leap in artificial intelligence and robotics. These models, mirroring the human brain's complexity and efficiency, have catalyzed innovations in machine learning, fostering more adaptive, intelligent, and efficient robotic systems. Recent research in areas like deep learning, reinforcement learning, and neural network optimization has significantly advanced, yet challenges remain, especially in robotics' real-world application, energy efficiency, and operation in complex, unstructured environments.
Keywords: neural network models, autonomous robotics, energy efficiency, Multi-Modal sensory data, Human-robot collaboration
Received: 04 Mar 2025; Accepted: 27 Mar 2025.
Copyright: © 2025 Cheng, Mao and Ward. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Long Cheng, North China Electric Power University, Beijing, China
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