Intelligent Robotics Systems: Current Developments and Future Prospects

Dear Colleagues,

Recent advances in artificial intelligence have revolutionized the field of robotics, enabling machines to perceive, decide, and act with unprecedented levels of autonomy and adaptability. This Special Issue aims to present cutting-edge research and visionary perspectives on intelligent robotic technologies that integrate deep learning, reinforcement learning, and deep reinforcement learning to achieve high-level decision-making and control.

The scope of this Special Issue covers a wide range of intelligent robotic systems, including autonomous ground, aerial, and underwater platforms designed for applications such as industrial automation, environmental monitoring, urban services, and healthcare assistance. Emphasis will be placed on AI-driven perception, multi-robot coordination, and adaptive decision-making in complex and dynamic environments.

We welcome contributions that explore novel algorithms, architectures, and system designs for intelligent robots, as well as studies that addres operational reliability and system validation. Both theoretical developments and experimental validations are encouraged.

Topics of interest include, but are not limited to, the following:

• Deep learning and reinforcement learning for robotic perception, control, and adaptive behaviors;
• Deep reinforcement learning for autonomous navigation, path planning, and real-time decision-making;
• Multi-agent and swarm robotics for coordinated tasks and distributed intelligence;
• Human–robot interaction, cognitive architectures, and collaborative autonomy;
• AI-driven autonomous systems for real-world and mission-critical applications;
• Intelligent sensing, multimodal perception, object recognition, and mission/adaptive planning;
• Robotic simulation, high-fidelity modeling, and digital-twin frameworks;
• Reliability, safety, and validation methodologies for AI-enabled robotic systems;
• Comparative studies of model-based vs. model-free reinforcement learning in physical robots;
• Multimodal sensor fusion for robust environmental understanding;
• Adaptive navigation and decision-making under uncertainty or dynamic environments;
• Decision-support systems for human–robot collaboration and manned–unmanned teaming;
• Physical AI for robust control, resilience, and real-world robotic operations.

In this Special Issue, we aim to highlight the current developments and future prospects of intelligent robotics, with a focus on the deepening integration of AI and robotics and its transformative impacts across a broad spectrum of civilian domains.

Dr. Jong-Hwan Kim
Dr. Joon-Hyuk Park
Prof. Dr. Namsuk Cho
Guest Editors

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• deep learning
• reinforcement learning
• robotic perception
• autonomous systems
• multi-robot coordination
• system validation
• simulation and digital twins