AI-Integrated Mechatronic Systems: Design, Control, and Applications

Mechatronic systems have evolved significantly with the rapid development of computational intelligence, advanced sensing, and autonomous control technologies. Traditionally relying on classical modelling and control approaches, modern mechatronics increasingly incorporates Artificial Intelligence and Machine Learning to achieve adaptive, data-driven functionality. These techniques enable systems to perceive their environment, learn from operational data, and optimize performance in real time. With growing demand for autonomy, precision, and efficiency across sectors such as manufacturing, robotics, transportation, and healthcare, AI-integrated mechatronics has become a pivotal research area. This special issue aims to highlight recent progress and emerging trends at the intersection of AI and mechatronics, promoting innovative solutions that enhance the intelligence, capability, and flexibility of next-generation mechanical systems.

The primary goal of this special issue is to address the growing need for intelligent, adaptive, and autonomous mechatronic systems capable of handling complex real-world environments. Traditional control and design approaches often fall short when systems must operate under uncertainty, interact dynamically with humans, or process large volumes of sensory data. Artificial Intelligence and Machine Learning offer powerful tools to overcome these limitations by enabling data-driven modeling, predictive decision-making, and self-optimizing control strategies.

Aim is to explore how AI can be systematically integrated into the design, control, sensing, and application of mechatronic systems to enhance performance, reliability, and autonomy. Recent advances such as deep learning-based perception, reinforcement learning for control, digital twins, and edge AI have opened new pathways for innovation in robotics, automation, smart manufacturing, and cyber-physical systems. By bringing together cutting-edge research from academia and industry, this collection seeks to identify emerging challenges, highlight novel solutions, and accelerate the adoption of AI-enabled mechatronic technologies across diverse engineering domains.

This Research Topic welcomes contributions that explore the integration of Artificial Intelligence and Machine Learning within mechatronic system design, modeling, sensing, control, and applications. Topics of interest include, but are not limited to,

1. AI-Based Intelligent Control in Mechatronics

2. Machine Learning in Robotics and Automation

3. Digital Twins and Cyber-Physical Systems

4. Computer Vision and Sensor Fusion

5. Bio-inspired and Nature-Inspired AI Techniques

6. Applications of AI in Mechatronic Domains

7. Medical mechatronics and rehabilitation robotics

We invite original research articles, reviews, perspective papers, and application-oriented case studies that present novel methodologies, theoretical advancements, experimental validations, or industrial-scale implementations. Manuscripts should clearly highlight the contribution’s significance, methodological rigor, and practical relevance to AI-enhanced mechatronic systems. Interdisciplinary works bridging mechanical engineering, robotics, control, and computational intelligence are especially welcome.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review

Keywords: Artificial Intelligence, Machine Learning, Intelligent Control, Mechatronic Systems, Robotics and Autonomous Systems, Smart Sensors and Actuators, Cyber-Physical Systems

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.