Generative AI and Robotics: Towards Intelligent and Adaptive Machines
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".
Deadline for manuscript submissions: 28 February 2026 | Viewed by 2
Special Issue Editors
Interests: artificial intelligence and autonomous technologies; machine learning; robot vision; autonomous vehicles and autonomous robots; Human–robot interaction; modeling and control
Special Issues, Collections and Topics in MDPI journals
Interests: mechatronics; parallel robots; robot programming; design of mechatronic systems; CAD; CAM; mechanisms and dynamics of machines; modelling and simulation; MATLAB/Simulink; VR; optimization; genetic algorithms
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in Generative Artificial Intelligence (GenAI) have opened new opportunities for robotics research and applications. From autonomous decision-making to simulation-based design, generative models—such as large language models (LLMs), diffusion models, and generative adversarial networks (GANs)—have begun to revolutionize how robots perceive, plan, and act.
This Special Issue aims to gather high-quality, original contributions that explore the synergy between Generative AI and Robotics, focusing on both theoretical foundations and practical implementations. We invite submissions that push the boundaries of current robotic capabilities by leveraging generative approaches.
Topics of Interest include, but are not limited to:
- Generative models for robotic control and planning
- Simulation-to-reality transfer using generative methods
- Language-guided robot manipulation and navigation
- Embodied AI with LLMs and vision-language models
- Generative design for soft and modular robotics
- Data augmentation and synthesis for robot learning
- Generative perception in unstructured environments
- Human-robot interaction enhanced by generative models
- Multi-robot systems and coordination using GenAI
- Safety, robustness, and explainability in generative robotics
Prof. Dr. Ayşegül Uçar
Dr. Sergiu Dan Stan
Guest Editors
Manuscript Submission Information
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Keywords
- generative models
- robotic
- human-robot interaction
- GenAI
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