Machine Learning and Cognitive Robotics
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 March 2026 | Viewed by 42
Special Issue Editors
Interests: service and personal robotics; medical and rehabilitational robotics; bio-inspired systems; humanoid robotics; biomechanics; two-legged walking; control systems; sensor systems and data collection from sensors; system integration
Interests: machine learning; biomedical engineering; neural network; image recognition
Interests: geometric modeling and simulation of the functioning of mechanical systems; computer-aided technological design of mechanical components; life expectancy estimates of mechanical components based on finite element analysis; developments regarding the mechanical system and drive system of robots with serial and parallel topology; programming of industrial robots
Special Issue Information
Dear Colleagues,
The focus of this Special Issue explores the intersection of Machine Learning (ML) and Cognitive Robotics, highlighting advancements in intelligent systems capable of perception, reasoning, learning, and interaction with humans and dynamic environments. The focus is on cutting-edge algorithms, cognitive architectures, and real-world applications that bridge AI and robotics. We invite contributions addressing (but not limited) to ML for Robotics (deep learning, reinforcement learning, and transfer learning in robotic control and decision-making), Cognitive Architectures (bio-inspired models, neuromorphic computing, and hybrid AI systems for autonomous robots), Human–Robot Interaction (HRI) (NLP, emotion recognition, and collaborative robotics), Ethics and Trust (explainable AI (XAI), safety, and fairness in cognitive robotic systems), Applications (healthcare robots, industrial automation, autonomous vehicles, and assistive technologies), etc. The purpose of the Special Issue is to showcase innovations integrating ML with cognitive robotics, fostering dialogue between researchers in AI, robotics, and cognitive science, as well as identifying challenges (e.g., real-time learning and adaptability) and future directions.
This collection will complement prior work, especially in relation to bridging the gaps in the knowledge. Many studies treat ML and robotics in isolation; we emphasize their synergy for adaptive, intelligent systems.
Prof. Dr. Miloš D. Jovanović
Dr. Jelena Vasiljevic
Dr. Calin-Octavian Miclosina
Guest Editors
Manuscript Submission Information
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Keywords
- machine learning (ML)
- cognitive robotics
- artificial intelligence (AI)
- autonomous systems
- human–robot interaction (HRI)
- deep learning
- reinforcement learning
- neural networks
- computer vision
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