Computer Vision and Machine Learning for Autonomous Intelligent Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 July 2026
Special Issue Editor
Special Issue Information
Dear Colleagues,
The field of autonomous intelligent systems is undergoing a paradigm shift, driven by rapid advancements in computer vision and machine learning. As we move beyond simple automation, the challenge lies in endowing agents—particularly autonomous vehicles, mobile robots, and humanoid platforms—with the ability to perceive, understand, and interact with complex, dynamic 3D environments in real time.
The aim of this Special Issue is to bring together innovative research at the intersection of visual perception and deep learning to enhance the autonomy of intelligent systems. We are particularly interested in methodologies that bridge the gap between raw sensory data and high-level cognitive reasoning, enabling robust navigation and interaction in the real world. Furthermore, we seek contributions focusing on the translation from metric 3D reconstruction to actionable semantic understanding, required for tasks such as vision–language navigation and complex manipulation. This includes the application of large foundation models to robotics (Embodied AI), advancements in 3D scene understanding, and the integration of vision with other modalities for improved decision-making.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Three-dimensional perception and scene understanding;
- Vision–language navigation (VLN) and semantic navigation;
- Manipulation in unstructured environments;
- Sim-to-real transfer learning for intelligent systems;
- Deep learning for humanoid robot control and locomotion.
I look forward to receiving your contributions.
Dr. Xiaoyan Li
Guest Editor
Manuscript Submission Information
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Keywords
- scene understanding
- autonomous navigation
- humanoid robotics
- embodied AI
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