Search Results (219)

Autonomous robots are increasingly integrated into social contexts, making affective human–robot interaction (HRI) critical for their effectiveness and acceptance. However, existing research remains dispersed across domains and techniques, lacking a unified framework to characterize core robotic capabilities. To address this gap, we adopt a capability-oriented perspective and conduct a comprehensive literature review, through which we propose a structured taxonomy of capabilities for robots in affective HRI. The taxonomy comprises five core dimensions: perception (recognizing human internal states), strategy (planning responses based on human states and context), expression (conveying robot lifelikeness and social presence), sustainability (maintaining effective and reliable operation over time), and ethics (ensuring behavior within ethical constraints). By organizing diverse research efforts into a structured framework, this taxonomy provides a systematic foundation for designing socially competent robots and guiding future research. Full article

The von Neumann architecture faces a “memory wall” problem due to the physical separation of memory and processor, posing major challenges to energy efficiency and latency in the era of artificial intelligence. To overcome these bottlenecks, artificial synaptic devices inspired by biological systems have emerged as an important research direction. By integrating sensing and computing functions at the device level, these architectures provide a promising approach for the efficient processing of natural physical signals. Supported by advances in functional materials and artificial neural network (ANN) algorithms, artificial synaptic devices are capable of perceiving and processing various external stimuli, showing strong potential for applications in intelligent electronic skins, robotics, and edge computing. This review provides a comprehensive overview of recent advances in artificial synaptic devices, with particular emphasis on tactile and visual sensing applications. We discuss representative device types and operating mechanisms, analyze critical challenges from the perspectives of material engineering and functional integration, and further summarize potential solutions and future trends toward multimodal sensory–memory–computing systems. Full article

As artificial intelligence (AI) as a technology becomes ever more pervasive in a wide range of human endeavor, from highly specialized technological and scientific applications to mass-market generative AI ‘consumed’ by the public, the question arises whether, over time, artificial intelligence could become cultural beings and, by extension, could develop a heritage of their own. This paper reopens a 2007 examination of whether future sentient robots, autonomous systems, or AI would possess culture, exercise cultural heritage and what conditions need to be met to reach that point. Based on two ‘conversations’ with two generative AI models, ChatGPT4.5 and DeepSeek R1, that examine the models’ ‘understanding’ of culture and heritage, we explored the various thematic and content connections these models make. This paper demonstrates the conditions, technological, attitudinal and societal that are required to allow for an AI culture to develop. That culture will look very different from that maintained by humans and will be based on very different, currently unknowable, value sets. This paper is novel, as it expands the conceptual framework of how we understand heritage from an anthropocentric perspective to one that includes non-human, ‘artificial’ intelligence now and in the future. Full article

This paper explores the interaction strategies of service robots in self-service shops from a user experience perspective in the case of robots with insufficient capabilities. A Yanshee robot and a self-developed localization-rotation system are employed as the experimental platform. A sales return in a self-service shop is employed as the experimental scenario. Two types of robot’s insufficient capabilities, three strategies of robots’ apology and a social interaction cue imitated from a human salesperson are considered in the design of interaction strategy between human and robot in this scenario. The results show that robots’ social insufficiency leads to more negative influence on customer experiences of fluency, comprehensibility, impression, intelligence, willingness for future interaction than robots’ performance insufficiency. An empathetic apology when the robot has insufficient performance is an effective interaction strategy. The interaction cue that the robot turns to face customers is not beneficial to customer experiences but does influence the internal relationship between customer experiences during HRI and after HRI. In the case of robots with social insufficiency in a self-service shop, impression, intelligence and interaction capability have positive impacts on the willingness for future interaction, while they are also positively affected by fluency or comprehensibility. In the case of robots with performance insufficiency, impression has a positive impact on willingness, while it is not directly related to fluency. The findings are valuable for informing the interaction design of service robots deployed in shopping, especially in real environments where performance and cost must be balanced. Full article

Generative Artificial Intelligence (GenAI), particularly Foundation Models (FMs), has recently become a key component of Industry 5.0. Despite growing interest in integrating these technologies into industrial environments, comprehensive analyses of the socio-technical opportunities and challenges of deploying these emerging AI systems in real-world settings remain limited. This article proposes a socio-technical conceptual perspective, termed Responsible Agentic Robotics (RAR), which structures the lifecycle deployment of agentic AI-enabled robotic systems around three core layers: context, design, and value. Additionally, this article presents a brief review of 21 peer-reviewed studies published between 2023 and 2025 (post-ChatGPT era) on FMs and agentic AI-enabled Human–Robot Collaboration (HRC) in industrial assembly/disassembly environments. The results indicate that existing research remains predominantly technology-centric, with a strong emphasis on enhancing robot autonomy, while comparatively limited attention is devoted to human-centered and responsible practices. Moreover, empirical evaluations of human, social, and sustainability dimensions, such as worker empowerment, human factors, well-being, inclusivity, resource utilization, and environmental impact, are rarely conducted and poorly discussed. This article concludes by identifying key socio-technical gaps, outlining future research directions. Full article

This paper presents a comprehensive review of quadruped robots in the construction industry, focusing on their applications, technological capabilities, and integration with digital construction workflows. Quadruped robots have emerged as promising mobile platforms due to their ability to traverse uneven terrain, operate autonomously, and support multimodal sensing, enabling tasks such as site inspection, 3D reality capture, safety monitoring, logistics support, and integration with Building Information Modeling (BIM) and digital-twin systems. Despite these advantages, real-world deployment remains constrained by limitations in battery endurance, payload capacity, communication reliability, perception robustness, and system interoperability. This review synthesizes findings from 20 studies published between 2015 and 2025 and incorporates a quantitative bibliometric analysis using both SciVal and Scopus. While SciVal provides performance-based indicators and global research trends, Scopus offers complementary publication coverage, improving analytical reliability. Unlike general robotics surveys, this review adopts a construction-centric perspective by explicitly linking quadruped robot capabilities to construction engineering objectives under practical site conditions. The findings highlight current application domains, technological gaps, and adoption barriers, and outline future research directions to support the effective integration of quadruped robots into construction practice. This review provides actionable insights for researchers, engineers, and practitioners assessing the readiness and limitations of quadruped robots in construction environments. Full article

Semantic point cloud maps play a pivotal role in smart agriculture. They provide not only core three-dimensional data for orchard management but also empower robots with environmental perception, enabling safer and more efficient navigation and planning. However, traditional point cloud maps primarily model surrounding obstacles from a geometric perspective, failing to capture distinctions and characteristics between individual obstacles. In contrast, semantic maps encompass semantic information and even topological relationships among objects in the environment. Furthermore, existing semantic map construction methods are predominantly vision-based, making them ill-suited to handle rapid lighting changes in agricultural settings that can cause positioning failures. Therefore, this paper proposes a positioning and semantic map reconstruction method tailored for orchards. It integrates visual, LiDAR, and inertial sensors to obtain high-precision pose and point cloud maps. By combining open-vocabulary detection and semantic segmentation models, it projects two-dimensional detected semantic information onto the three-dimensional point cloud, ultimately generating a point cloud map enriched with semantic information. The resulting 2D occupancy grid map is utilized for robotic motion planning. Experimental results demonstrate that on a custom dataset, the proposed method achieves 74.33% mIoU for semantic segmentation accuracy, 12.4% relative error for fruit recall rate, and 0.038803 m mean translation error for localization. The deployed semantic segmentation network Fast-SAM achieves a processing speed of 13.36 ms per frame. These results demonstrate that the proposed method combines high accuracy with real-time performance in semantic map reconstruction. This exploratory work provides theoretical and technical references for future research on more precise localization and more complete semantic mapping, offering broad application prospects and providing key technological support for intelligent agriculture. Full article

Robotic-assisted surgery (RAS) provides enhanced dexterity and visualisation but remains constrained by the absence of clinically meaningful palpation and haptic feedback. This perspective examines palpation sensing in RAS from an engineering and system-integration standpoint, identifying the lack of tactile information as a major contributor to increased cognitive load, prolonged training, and risk of tissue injury. Recent advances in force, tactile, vibroacoustic, audio, and optical sensor technologies enable quantitative assessment of tissue mechanical properties and often exceed human tactile sensitivity. However, clinical translation is limited by challenges in sensor miniaturisation, sterilisation, robustness and integration and the absence of standardised evaluation metrics. The integration of artificial intelligence and multimodal sensor fusion with intra-operative imaging and augmented visualisation is highlighted as a key strategy to compensate for sensor limitations and biological variability. Dedicated robotic palpation devices and wireless or magnetically coupled probes are discussed as promising transitional solutions. Overall, the restoration of palpation sensing is presented as a prerequisite for improving safety and efficiency and enabling higher levels of autonomy in future RAS platforms. Full article

The intelligent surgical knife (iKnife), based on rapid evaporative ionization mass spectrometry (REIMS), represents a transformative advance in intraoperative tissue characterization. By integrating mass spectrometry with electrosurgical dissection, the iKnife enables real-time differentiation between cancerous and healthy tissues through molecular fingerprinting of the aerosol generated during cutting. This innovation significantly shortens operative time by eliminating delays associated with conventional histopathological analysis and enhances surgical precision by providing continuous feedback on tissue composition. Since its inception by Zoltán Takáts and colleagues, the iKnife has demonstrated remarkable diagnostic accuracy across multiple cancer types, including breast, ovarian, and colorectal malignancies, with reported sensitivities and specificities > 90% in selected tumour types. Beyond oncology, REIMS technology also shows promise for microbial identification and metabolomic profiling. This review provides a comprehensive overview of the iKnife’s development, underlying principles, clinical validation, and emerging applications, as well as its integration into surgical workflows and the challenges remaining for widespread clinical adoption. Future perspectives include miniaturization, AI-driven spectral interpretation, and expansion into robotic and image-guided surgery. Full article

This study analyzes the ICT infrastructure in teaching practice centers from the perspective of students enrolled in early childhood and primary education degree programs at a Spanish university during the 2024–2025 academic year. A quantitative, cross-sectional design was employed. A questionnaire was distributed to all first- to fourth-year students via the university platform, with a sample of 556 participants. The data collection instrument consisted of an ad hoc adaptation and extension of the validated EdSocEval_V2 questionnaire, ensuring factorial validity. It was used to examine the availability of technological resources for communication and digital management, together with personal and contextual variables to support data classification. Results indicate high availability of basic digital resources, including projectors, Wi-Fi, interactive whiteboards, printers, alongside limited access to robotics, digital tablets, and classrooms of the future. High homogeneity was observed in communication and digital management resources, such as websites, virtual learning environments and corporate email. MANOVA analyses revealed that students perceive ICT infrastructure to be more integrated at higher levels of primary education, with no significant differences based on school ownership. Binary logistic regressions showed that school ownership predicts the availability of certain ICT resources, with private schools exhibiting lower network presence. Full article

Background/Objectives: Pelvic exenteration is a radical procedure performed for recurrent gynecologic cancers. The goal of exenteration is to prolong survival, but this procedure also results in extensive tissue loss and consequently high morbidity. Reconstruction using vascularized flaps, particularly the VRAM flap, is crucial to restoring pelvic integrity and decreasing complications resulting from extensive tissue loss. With the rise of minimally invasive surgery, the traditionally open abdominal approach to exenteration and reconstruction can now be performed with the assistance of robotic platforms. This review aims to summarize available evidence, describe techniques, and propose future directions for robotic rectus flap reconstruction after pelvic exenteration. Methods: This narrative review was conducted following the SANRA guidelines for narrative synthesis. A comprehensive search of PubMed, Embase, Scopus, and Web of Science was conducted for studies published between January 2000 and November 2025 on pelvic exenteration followed by robotic rectus abdominis flap reconstruction in gynecologic oncology. Eligible studies were retrospective or prospective reports, technical descriptions, case series, or comparative analyses. Non-robotic techniques and animal studies were excluded. Although the primary focus was gynecologic oncology, technically relevant studies from other oncologic disciplines were included when the reconstructive approach was directly applicable to pelvic exenteration. Extracted data included patient demographics, surgical details, and perioperative and oncologic outcomes. Results: The literature search identified primarily case reports and small single-center series describing robot-assisted rectus muscle-based flap reconstruction after pelvic exenteration. Reported cases demonstrated technical feasibility and successful flap harvest using robotic platforms, with adequate pelvic defect coverage. Potential benefits, such as reduced wound morbidity and preservation of a minimally invasive workflow, have been described. However, patient numbers were small, techniques varied, and standardized outcome measures or comparative data with open approaches were lacking. Conclusions: Robotic rectus flap reconstruction represents a promising advancement in pelvic exenteration surgery, potentially reducing morbidity and improving recovery. Further research, including multicenter prospective studies, is needed to validate these findings and establish standardized protocols. Full article

The establishment of a sustained human presence on the Moon is critically dependent on the ability to utilize local resources, primarily the production of oxygen for life support and propellant. The ROXY (Regolith to Oxygen and metals conversion) process is a molten salt electrolysis technology designed for this purpose. This paper presents an economic analysis of a ROXY pilot plant capable of producing over one ton of oxygen per year. We evaluate the economic viability by analyzing development, transportation, and operational costs against the potential revenue from selling oxygen and metals within a nascent lunar economy. A key aspect of this analysis is the perspective of an early customer in habitation life support systems preceding that of much higher propellant production demand. The analysis contextualizes this paradigm by recognizing that the primary economic driver for oxygen production is the larger future market for propellant; however, early life support demand may incentivize a paradigm-shift from Earth-based consumable resupply. Scenarios based on varying transportation costs and development timelines are evaluated to determine the internal rate of return (IRR) and time to break even (TTBE). The results indicate that the ROXY pilot plant is economically viable, particularly in near-term scenarios with higher transportation costs, achieving a positive IRR of up to 47.4% when both oxygen and metals are sold. The analysis identifies facility mass, driven by the robotics subsystem, as the primary factor for future cost-reduction efforts, concluding that ROXY is a technically and economically sound pathway toward sustainable lunar operations. Full article

The widespread application of robots in complex and dynamic environments demands that Visual SLAM is both robust and accurate. However, dynamic objects, varying illumination, and environmental complexity fundamentally challenge the static world assumptions underlying traditional SLAM methods. This review provides a comprehensive investigation into the mathematical foundations of V-SLAM and systematically analyzes the key optimization techniques developed for dynamic environments, with particular emphasis on advances since 2020. We begin by rigorously deriving the probabilistic formulation of V-SLAM and its basis in nonlinear optimization, unifying it under a Maximum a Posteriori (MAP) estimation framework. We then propose a taxonomy based on how dynamic elements are handled mathematically, which reflects the historical evolution from robust estimation to semantic modeling and then to deep learning. This framework provides detailed analysis of three main categories: (1) robust estimation theory-based methods for outlier rejection, elaborating on the mathematical models of M-estimators and switch variables; (2) semantic information and factor graph-based methods for explicit dynamic object modeling, deriving the joint optimization formulation for multi-object tracking and SLAM; and (3) deep learning-based end-to-end optimization methods, discussing their mathematical foundations and interpretability challenges. This paper delves into the mathematical principles, performance boundaries, and theoretical controversies underlying these approaches, concluding with a summary of future research directions informed by the latest developments in the field. The review aims to provide both a solid mathematical foundation for understanding current dynamic V-SLAM techniques and inspiration for future algorithmic innovations. By adopting a math-first perspective and organizing the field through its core optimization paradigms, this work offers a clarifying framework for both understanding and advancing dynamic V-SLAM. Full article

Various recurring medical events encourage innovative patient well-being through connected health strategies based on an elegant digital environment that prioritizes safety, comfort, and beneficial outcomes for both patients and medical staff. This narrative review article aims to investigate and highlight the potential of advanced, reliable, high-precision, and secure medical observation and intervention missions. These involve a smart digital environment integrating smart materials combined with smart digital monitoring. These medical implications concern robotic surgery and drug delivery through image-assisted implantation, as well as wearable observation and assistive tools. The former requires high-precision motion and positioning strategies, while the latter enables sensing, diagnosis, monitoring, and central task assistance. Both advocate minimally invasive or noninvasive procedures and precise supervision through autonomously controlled processes with staff participation. The article analyzes the requirements and evolution of medical interventions, robotic actuation technologies for positioning actuated and self-moving instances, monitoring of image-assisted robotic procedures using digital twins and augmented digital tools, and wearable medical detection and assistance devices. A discussion including future research perspectives and conclusions complete the article. The different themes addressed in the proposed paper, although self-sufficient, are supported by examples of the literature, allowing a deeper understanding. Full article

The increasing complexity of marine operations has intensified the need for intelligent robotic systems to support ocean observation, exploration, and resource management. Underwater swarm robotics offers a promising framework that extends the capabilities of individual autonomous platforms through collective coordination. Inspired by natural systems, such as fish schools and insect colonies, bio-inspired swarm approaches enable distributed decision-making, adaptability, and resilience under challenging marine conditions. Yet research in this field remains fragmented, with limited integration across algorithmic, communication, and hardware design perspectives. This review synthesises bio-inspired coordination mechanisms, communication strategies, and system design considerations for underwater swarm robotics. It examines key marine-specific algorithms, including the Artificial Fish Swarm Algorithm, Whale Optimisation Algorithm, Coral Reef Optimisation, and Marine Predators Algorithm, highlighting their applications in formation control, task allocation, and environmental interaction. The review also analyses communication constraints unique to the underwater domain and emerging acoustic, optical, and hybrid solutions that support cooperative operation. Additionally, it examines hardware and system design advances that enhance system efficiency and scalability. A multi-dimensional classification framework evaluates existing approaches across communication dependency, environmental adaptability, energy efficiency, and swarm scalability. Through this integrated analysis, the review unifies bio-inspired coordination algorithms, communication modalities, and system design approaches. It also identifies converging trends, key challenges, and future research directions for real-world deployment of underwater swarm systems. Full article