Next-Generation Robotic Intelligence: Active Perception, Adaptive Collaboration and Cross-Domain Digital Twins

Dear Colleagues,

Recent advances in robotics are rapidly transforming the way intelligent machines perceive, interact with, and respond to complex environments. This Special Issue, titled “Next-Generation Robotic Intelligence: Active Perception, Adaptive Collaboration and Cross-Domain Digital Twins”, will bring together cutting-edge research at the intersection of high-fidelity perception, intelligent control, human–robot collaboration, and integrated digital twin technologies.

This topical collection aims to explore novel computational, algorithmic, and architectural methods that enable robots to operate with higher levels of autonomy, safety, and situational awareness. Particular attention is given to perception or active perception, where robots purposefully select viewpoints or actions to improve sensory understanding, adaptive collaboration, where robots dynamically adjust their behaviour in shared human–robot or multi-robot tasks, and cross-domain digital twins, which link physical systems, human factors, and environmental models into unified, real-time virtual representations.

The scope of this Special Issue includes foundational theories, technological innovations, system architectures, experimental validations, and application-oriented studies. Relevant domains include industrial manufacturing, construction, agriculture, logistics, healthcare, field robotics, and service robotics, as well as emerging cyber–physical and human-centric environments. Contributions may address perception-driven control, multi-modal sensor fusion, predictive planning, simulation-based optimisation, behaviour learning, and digital twin-enabled monitoring and decision support.

The purpose of this Special Issue is to provide a comprehensive platform on which researchers and practitioners may present advancements that redefine modern robotic intelligence. By integrating active perception strategies, adaptive collaborative control, and digital twin-based reasoning, this collection aims to highlight the next wave of robotics research capable of bridging the gap between laboratory-level performance and real-world deployment.

This collection will supplement the existing literature by emphasising the synergy among perception, collaboration, and digital twin technologies—three pillars often addressed independently in past research. By curating interdisciplinary contributions, this Special Issue seeks to establish a coherent understanding of how these elements jointly contribute to safer, more responsive, and more robust robotic systems.

We warmly invite original research, surveys, and application papers that advance this fast-evolving field.

Dr. Vasiliki Balaska
Dr. Katerina Maria Oikonomou
Prof. Dr. Antonios Gasteratos
Guest Editors

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• perception (or active perception)
• multimodal sensor fusion
• adaptive human–robot collaboration
• multi-robot coordination
• digital twins for robotics
• intelligent robotic control
• cognitive robotics
• predictive modelling and simulation
• AI-driven decision making
• cyber–physical systems