International Journal of Humanoid Robotics

Call for Papers

Summary

The rapid advancements in artificial intelligence (AI), robotics and the Internet of Things (IoT) are transforming smart home environments making them more efficient, responsive and adaptive. Among these innovations, cognitive humanoid robots are emerging as a critical technology for home automation, intelligent assistance and personalized services. These robots are designed to interact naturally with humans, perform household tasks and adapt to dynamic environments, making them essential for elderly care, smart living and independent assistance. The integration of deep learning, reinforcement learning, multimodal sensor fusion and real-time decision-making enables humanoid robots to perceive, learn, and autonomously execute complex tasks in home settings. Human-robot collaboration, adaptive control systems, and emotion-aware AI enhance the effectiveness of these robots, allowing them to provide personalized and context-aware assistance. However, achieving full autonomy, situational awareness, and ethical AI decision-making in home environments presents significant challenges.

The deployment of cognitive humanoid robots in smart homes faces technical, ethical and practical obstacles. One of the key challenges is real-time perception and situational awareness, as robots must navigate complex household environments filled with dynamic obstacles, varying lighting conditions and unpredictable human interactions. Advanced sensor fusion techniques integrating visual, auditory and tactile data are essential for seamless navigation, object recognition and precise manipulation. Additionally, adaptive learning models enable robots to refine their actions continuously based on user behaviour, environmental changes and personalized preferences.

Human-robot interaction (HRI) is crucial in household robotics, requiring voice recognition, gesture interpretation and natural language processing (NLP) for intuitive and user-friendly communication. Cognitive robots must understand context, respond effectively and anticipate user needs, making AI-driven personalization a vital aspect of smart home integration. Additionally, their ability to detect and respond to human emotions enhances their role as assistive companions particularly for elderly individuals and rehabilitation support. Safety, security and ethical considerations are paramount for trustworthy AI-driven home assistants. Ensuring privacy-preserving AI models that protect user data and interactions is critical. Robots must also adhere to strict safety standards to prevent accidents and unintended harm. Developing explainable AI (XAI) models will improve transparency helping users understand robotic decisions and fostering trust in autonomous assistance.

This Special Issue aims to advance research on AI-driven cognitive humanoid robots for smart homes, focusing on autonomy, adaptability, and seamless home integration. It seeks contributions that explore IoT-enabled automation, proactive health monitoring, human-robot interaction, and ethical AI frameworks, driving innovative solutions for next-generation assistive and intelligent home robotics.

The topics of the issue include but not limited to the following:

• Human-Robot Interaction in Smart Homes.
• Sensor Fusion and Perception in Home-Based Humanoid Robotics.
• Emotion-Aware AI and Personalized Assistance in Home Automation.
• AI-Powered Household Task Automation.
• Assistive Cognitive Robots for Elderly Care and Independent Living.
• Privacy, Security, and Ethical AI in Home Robotics.
• Adaptive Learning and Behaviour Modelling for Home Assistance.
• Proactive Health Monitoring and Emergency Response.
• AI and Deep Learning for Cognitive Humanoid Robots in Home Environments.
• AI-Enhanced Smart Home Integration and Personalized Automation.
• Human-in-the-Loop Learning for Household Robotics.
• Explainable AI (XAI) for Trustworthy Humanoid Robots in Home Environments.
• Future Trends in Cognitive Humanoid Robotics for Smart Homes.

Guest Editor Details:

Prof. Pawel Skruch
Department of Automatic Control and Robotics,
AGH University of Krakow, Poland
Email: masterskpawel@gmail.com, skruch@agh.edu.pl
Google Scholar: https://scholar.google.com/citations?user=tuCKmRwAAAAJ&hl=en

Short Bio: Pawel Skruch (Senior Member, IEEE) received the M.S. degree (Hons.) in automation control and the Ph.D. degree (summa cum laude) from the Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, AGH University of Science and Technology, Krakow, Poland, in 2001 and 2005, respectively, and the D.Sc. (Habilitation) degree in automatics and robotics from the AGH University, in 2016. He is currently a Professor of control engineering with the AGH University of Science and Technology and also the Advanced Engineering Manager AI and Safety with the Aptiv Technical Center, Krakow. His current research interests include dynamical systems, autonomous systems, artificial intelligence, machine learning, modeling and simulation, and applications of control theory to software systems.

Prof. Saleh Mobayen
Graduate School of Intelligent Data Science,
National Yunlin University of Science and Technology,
Douliou, Yunlin 640301, Taiwan
Email: mobayens@yuntech.edu.tw
Google Scholar: https://scholar.google.com/citations?user=LzZ-OSoAAAAJ&hl=en

Short Bio: Saleh Mobayen (Senior Member, IEEE) was born in Khoy, Iran, in 1984. He received the B.Sc. and M.Sc. degrees in Electrical Engineering, area: Control Engineering, from the University of Tabriz, Tabriz, Iran, in 2007 and 2009, respectively, and received his Ph.D. degree in Electrica Engineering, area: Control Engineering, from Tarbiat Modares University, Tehran, Iran, in January 2013. Currently, he is Associate Professor at the National Yunlin University of Science and Technology (YunTech), Taiwan, and collaborated with the Future Technology Research Center (FTRC). He has published several papers in the national and international journals. His research interests include control theory, sliding mode control, robust tracking, non-holonomic robots and chaotic systems.

Prof. Marek Galinski
Institute of Computer Engineering and Applied Informatics,
Slovak University of Technology in Bratislava,
Bratislava, Slovakia.
Email: marek.galinski@stuba.sk
Google Scholar: https://scholar.google.co.uk/citations?user=LuzEJIcAAAAJ&hl=en

Short Bio: Marek Galinski (Member, IEEE) received the Ph.D. degree from FIIT, STU, Bratislava, in 2020. He is currently an Associate Professor with FIIT, STU. He is also the Head of the Automotive Innovation Laboratory, FIIT, STU. He is the coauthor of book focused on both technical and legal aspects of the cybersecurity of automated vehicles, which has been written in cooperation with the Faculty of Law, Comenius University in Bratislava and published in Wolters Kluwer. With research focused mainly on V2X communications and intelligent mobility in terms of communication architectures and computer networks optimization or security. Together with an interest in LEO satellite networks and new generations of cellular networks, he is focused on the management of heterogeneous networks in terms of low latency and reliability for safety-critical applications in the V2X environment.

Important Dates:

• Submission of papers: 10th August, 2025
• Notification to the authors: 10th October, 2025
• Revision deadline for papers: 10th December, 2025
• Final notification: 31th January, 2026