AI-Powered Robotic Systems: Learning, Perception and Decision-Making
A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "AI in Robotics".
Deadline for manuscript submissions: 28 February 2026 | Viewed by 7
Special Issue Editors
Interests: grasping; manipulation; industrial robot; humanoid robot
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent robots with a focus on brain-machine interface; evolutionary robotics; map building; multi-robot systems; humanoid robot
Special Issues, Collections and Topics in MDPI journals
Interests: computational intelligence and fuzzy systems; intelligent data analysis; smart industry; applications in energy and healthcare
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in artificial intelligence (AI) have dramatically transformed the capabilities of robotic systems, enabling them to perceive complex environments, learn from experience, and make autonomous decisions in real time. The integration of machine learning, deep learning, and probabilistic reasoning into robotics has led to substantial progress in various domains, including autonomous navigation, human–robot interaction, manipulation, and swarm coordination.
This Special Issue aims to bring together cutting-edge research and innovative applications of AI and robotics, with a particular focus on learning algorithms, perceptual systems, and decision-making frameworks.
Topics of interest include, but are not limited to, the following:
- Learning-based control and planning for robotics;
- Perception and sensor fusion using AI techniques;
- Reinforcement learning and imitation learning in robotics;
- Vision-based navigation and manipulation;
- Real-time decision-making under uncertainty;
- Cognitive robotics and adaptive behaviors;
- Multi-agent coordination and decision-making;
- AI applications in human–robot interaction;
- Applications in service robotics, field robotics, healthcare, manufacturing, and more.
We welcome original research articles, comprehensive reviews, and case studies that address theoretical foundations, algorithm development, system implementations, and real-world deployments of AI-powered robotic systems. This Special Issue aims to provide a comprehensive overview of recent developments in the next generation of intelligent robots.
Prof. Dr. Kensuke Harada
Prof. Dr. Genci Capi
Prof. Dr. João Miguel da Costa Sousa
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 100 words) can be sent to the Editorial Office for announcement on this website.
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. Robotics is an international peer-reviewed open access monthly 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 1800 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
- learning-based control
- planning for robotics
- perception and sensor fusion
- reinforcement learning
- vision-based navigation
- decision-making
- cognitive robotics
- adaptive behaviors
- multi-agent
- AI applications in human–robot interaction
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