Intelligent Robotics: Design and Applications

1. Introduction

With the rapid development of information technology and, in particular, artificial intelligence (AI), intelligent robotics has entered a phase of accelerated growth [1,2]. The increasing demand for intelligent robots spans numerous domains, including education, healthcare, finance, catering, tourism, manufacturing, and transportation [3,4]. These systems take various forms, ranging from virtual intelligent agents (e.g., AI tutors) to physical intelligent robots (e.g., service and logistics robots used in hospitality and industrial environments) [5,6]. In parallel, intelligent robotics is playing a growing role in advancing the United Nations Sustainable Development Goals (SDGs) by reducing human exposure to high-risk tasks, enabling more efficient resource management, and supporting inclusive access to education and healthcare [7,8].

The evolution of intelligent robotics is being fueled by several technological drivers. Advances in machine learning and deep neural networks have enabled robots to perceive their environments more accurately and adaptively [9,10]. Sensor technologies such as Light Detection and Ranging (LiDAR), depth cameras, and tactile sensors provide unprecedented levels of situational awareness [11,12]. Emerging paradigms such as digital twin frameworks integrate physical robots with real-time virtual models, allowing for predictive maintenance, simulation-based optimization, and enhanced safety monitoring [13,14]. Furthermore, human–robot interaction (HRI) research has evolved from basic command-and-control systems to more natural, multimodal communication channels that involve speech, gestures, affective computing, and even emotional sound design [15,16].

The societal and industrial relevance of intelligent robots is increasingly visible. In education, intelligent tutoring agents are reshaping personalized learning and lifelong training [17,18]. In healthcare, assistive robots support elderly care, rehabilitation, and remote diagnostics [19,20]. In industrial manufacturing and logistics, autonomous mobile robots (AMRs), collaborative robots (cobots), and intelligent warehouses are transforming production efficiency [21,22]. In public services, robots deployed in hotels, airports, and hospitals are improving customer experiences through automated check-in, delivery, and cleaning tasks [23,24]. The convergence of these applications demonstrates how intelligent robotics is no longer confined to laboratory prototypes but is instead becoming a cornerstone of smart cities and Industry 4.0 ecosystems [25,26].

Despite these advances, several challenges remain at the forefront. Ensuring safety and reliability in unstructured and complex environments is an ongoing concern, particularly when robots collaborate directly with humans [27,28]. Building trust and social acceptance requires addressing ethical considerations, transparency in AI decision-making, and designing robots that respect cultural norms and human comfort [29,30]. The integration of generative AI opens new opportunities for creativity, adaptability, and natural interaction, yet it also introduces risks related to control, explainability, and misuse [31,32]. Another pressing issue is the persistent gap between industrial practice and standardization frameworks, as regulations often lag behind technological innovations, leading to uncertainties in deployment and adoption [33,34]. Addressing these challenges requires cross-disciplinary collaboration that bridges engineering, computer science, psychology, and social sciences [35,36].

In this context, the Special Issue Intelligent Robotics: Design and Applications brings together diverse contributions that reflect the state of the art in robot design, application, and societal integration. The papers in this collection showcase novel approaches ranging from digital-twin-based industrial robots to affective communication in social robots, autonomous warehouse systems, safety analysis of quadruped robots, and dynamic proxemic models for human–robot interaction [37,38,39,40,41]. Collectively, these works highlight not only the technological frontiers of intelligent robotics but also the broader implications for sustainability, industry transformation, and human–robot coexistence. The following overview highlights the key themes and findings of the papers published in this collection.

2. An Overview of Published Articles

The contributions to this Special Issue reflect the broad spectrum of approaches currently shaping the field of intelligent robotics. A first line of work emphasizes the integration of digital twin frameworks into robotic systems [37]. This study demonstrates the potential of coupling physical robots with real-time virtual models. In particular, industrial applications, such as cleaning operations in hazardous nuclear environments, can be optimized for efficiency, safety, and predictive control. Enhanced path-planning strategies and simulation-based monitoring show how digital twins can significantly reduce energy consumption and operational risks while paving the way for scalable deployment in complex industrial scenarios.

In parallel, research on affective communication for social robots illustrates the growing importance of human-centered design [38]. Instead of relying solely on speech or visual cues, robots are increasingly equipped with non-linguistic utterances (NLUs) and affective sound design generated through machine learning techniques. Experimental validation with human participants indicates that such sounds can reliably convey emotional valence and arousal, offering robots language-independent channels for interaction. This innovation broadens the cultural accessibility of social robots and underlines the need to consider multimodal, emotion-sensitive interfaces in human–robot interaction research.

From an industrial logistics perspective, the introduction of the Autonomous Industrial Mobile Warehouse (AIMW) provides an important step toward rethinking how spare parts and materials are distributed in large-scale factories [39]. Unlike conventional Automated Guided Vehicles (AGVs) or Autonomous Mobile Robots (AMRs), the AIMW replaces static storage systems with mobile and adaptive warehouses, reducing delays in maintenance and increasing overall flexibility. At the same time, these implementations reveal significant gaps between research prototypes and existing industrial standards, pointing to the urgent need for updated regulatory frameworks that can keep pace with technological innovation.

The Special Issue also addresses the pressing issue of safety in collaborative robotics, particularly in relation to quadruped robots deployed in smart factories [40]. By combining operator surveys with Delphi-based expert consultations, researchers identified collision, path deviation, and sensor reliability as critical risk factors. Moreover, the analysis revealed distinct differences in risk perception between developers, safety experts, and end-users, which highlights how stakeholder background influences expectations and concerns. These insights demonstrate that technical solutions alone are insufficient, and that effective deployment requires collaboration among engineers, industry practitioners, and policymakers, as well as tailored education and training initiatives.

Finally, research on dynamic proxemic models introduces a novel human-centered perspective to robot navigation and interaction [41]. By leveraging the golden ratio to define adaptive comfort and safety zones, these models allow robots to modulate their behavior in response to human position, orientation, and motion. Experiments conducted with both quadruped and wheeled robots confirmed that such approaches not only improve physical safety but also increase perceived comfort and acceptance among human users. This work points to a new generation of socially aware robots capable of respecting psychological as well as physical boundaries in shared spaces.

Taken together, the articles in this Special Issue illustrate how intelligent robotics is advancing along complementary directions: enhancing autonomy and efficiency in industrial applications, enriching emotional and social capabilities in human-centered contexts, addressing safety and regulatory concerns in collaborative environments, and embedding social awareness into navigation and interaction models. Collectively, they highlight the interdisciplinary character of the field, demonstrating how progress in intelligent robotics increasingly requires the integration of engineering, AI, human factors, and policy considerations.

3. Conclusions

The contributions to this Special Issue collectively highlight the accelerating pace and widening scope of intelligent robotics research. The studies reviewed here illustrate how emerging technologies, such as digital twins, affective interaction models, autonomous mobile warehouses, collaborative safety assessments, and dynamic proxemic frameworks, are shaping both industrial and social dimensions of robotics. These works confirm that intelligent robotics is no longer an isolated technical discipline but rather an inherently interdisciplinary field that requires the integration of engineering, computer science, cognitive psychology, ethics, and policy [42]. At the same time, they demonstrate that progress must be evaluated not only in terms of technical performance but also in relation to human acceptance, regulatory compliance, and sustainable development [43].

Looking forward, several key directions emerge. First, further work is needed to strengthen the link between digital and physical systems, enabling predictive maintenance and large-scale deployment of robots in hazardous and mission-critical environments [44]. Second, advances in human–robot interaction should extend beyond functional communication to encompass affective, cultural, and ethical dimensions, ensuring that robots can operate in diverse social contexts [45]. Third, the rapid growth of autonomous logistics and collaborative robots underscores the urgency of developing updated regulatory frameworks and international standards that can guide safe and equitable deployment [46]. Fourth, there is a growing need to design robots that are not only technically capable but also socially aware, integrating adaptive proxemic models, explainable AI, and context-sensitive learning mechanisms to build trust with human users [47]. Finally, the alignment of intelligent robotics with the Sustainable Development Goals (SDGs) should be further strengthened, positioning robots as enablers of environmental sustainability, inclusive education, and equitable healthcare [48].

In conclusion, the works included in this Special Issue demonstrate both the promise and complexity of intelligent robotics. They provide a foundation for future exploration but also call for more ambitious, interdisciplinary, and human-centered research agendas. It is expected that continued efforts in these directions will foster the development of intelligent robotic systems that are efficient, safe, and adaptive, while also being ethical, socially accepted, and globally impactful.