Blockchain ecosystems are rapidly maturing and meeting the needs of business environments (e.g., industry, manufacturing, and robotics). The decentralized approaches in industries enable novel business concepts, such as machine autonomy and servitiza...
Human–machine interaction (HMI) has become a central issue in autonomous driving because partial automation can degrade, rather than improve, human performance during takeover, handover, and out-of-the-loop transitions. Similar interaction risk...
In this review, our goal is to design and test quantum-like algorithms for Artificial Intelligence (AI) in open systems to structure a human–machine team to be able to reach its maximum performance. Unlike the laboratory, in open systems, teams...
This article will examine the unnamed and potentially devastating constraining effect of software on human autonomy. I call this concept residual causality, where software design decisions made long ago in different circumstances for different reason...
We review the progress in developing a science of interdependence applied to the determinations and perceptions of risk for autonomous human–machine systems based on a case study of the Department of Defense’s (DoD) faulty determination o...
A mega constellation of Nano/microsatellites is the contemporary solution for global-level Earth observation demands. However, as most of the images taken by Earth-observing satellites are covered by clouds, storing and downlinking these images resul...
This paper presents the findings of detailed and comprehensive technical literature aimed at identifying the current and future research challenges of tactical autonomy. It discusses in great detail the current state-of-the-art powerful artificial in...
Autonomy in maritime operations has increased, especially through advancements in Maritime Autonomous Surface Ships (MASS). Despite technical progress, there’s a gap in understanding how human involvement affects safety during transitions betwe...
With the rapid development of electric Vertical Take-Off and Landing (eVTOL) aircraft for urban air mobility, ensuring safe operation in complex low-altitude environments remains a major challenge. In particular, interactions with non-cooperative air...
Advances in machine learning, predictive analytics, and clinical prediction modeling have accelerated the development of algorithmic tools for estimating reproductive outcomes after cancer treatment. In female oncofertility counseling, these models m...
This article reflects on explainability in the context of medical artificial intelligence (AI) applications, focusing on AI-based clinical decision support systems (CDSS). After introducing the concept of explainability in AI and providing a short ov...
Human–autonomy teams (HATs) incorporating uncrewed aerial systems (UASs) play critical roles in a variety of safety-critical systems. Increased autonomy in HATs in beyond visual line of sight (BVLOS) UAS operations introduces new mission, safet...
Next-generation space observatories for high-energy gamma-ray astrophysics will increase scientific return using onboard machine learning (ML). This is now possible thanks to today’s low-power, radiation-tolerant processors and artificial intel...
Biomarker-based predictive tests for subjectively asymptomatic Alzheimer’s disease (AD) are utilized in research today. Novel applications of artificial intelligence (AI) promise to predict the onset of AD several years in advance without determining...
This work describes an assistive technology development for cognitive support and training to be used by children of special education schools in Spain. Design is based on and guided by cognitive support findings coming from a long-term collaboration...
Industry 5.0 combines automation/digitalization with human capabilities to create a more intuitive, interactive, and sustainable working environment. Additive manufacturing, widely known as 3D printing, is a key technology used to increase customizat...
Evidence-based medicine integrates results from randomized controlled trials (RCTs) and meta-analyses, combining the best external evidence with individual clinical expertise and patients’ preferences. However, RCTs of surgery differ from those...
Visual teach and repeat navigation (VT&R) is popular in robotics thanks to its simplicity and versatility. It enables mobile robots equipped with a camera to traverse learned paths without the need to create globally consistent metric maps. Altho...
The performance of deep neural networks and the low costs of computational hardware has made computer vision a popular choice in many robotic systems. An attractive feature of deep-learned methods is their ability to cope with appearance changes caus...
The performance of deep learning-based detection methods has made them an attractive option for robotic perception. However, their training typically requires large volumes of data containing all the various situations the robots may potentially enco...
Background: With the availability of extensive health data, artificial intelligence has an inordinate capability to expedite medical explorations and revamp healthcare.Artificial intelligence is set to reform the practice of medicine soon. Despite th...
Two key pillars of human-centered AI (HCAI) approaches are “control” and “autonomy”. To date, little is known about professional translators’ attitudes towards these concepts in the AI era. This paper explores this issue...
This paper details the design of a guidance architecture, in the form of a layered, finite state machine, meant to enable safe and autonomous rendezvous operations. The onboard software uses relative state parametrization based on relative orbital el...
According to the Church–Turing thesis, the limit of what is computable is bounded by Turing machines. Following from this, given that general computable functions formally describe the notion of recursive mechanisms, it is sometimes argued that...
Benchmark-driven evaluation helps distinguish between planning quality and interface reliability when large language models are utilized for embodied reasoning in simulation. Our submission to the Embodied Agent Interface Challenge (EAI) is evaluated...
Heavy-load unmanned aerial vehicles (UAVs) are increasingly being applied in logistics, infrastructure installation, and emergency response missions, where complex payload dynamics and unstructured environments pose significant challenges to safe and...
We develop a new theory of knowledge with mathematics and a broad-based series of case studies to seek a better understanding of what constitutes knowledge in the field and its value for autonomous human–machine teams facing uncertainty in the...
The advent of autonomous vehicles has heralded a transformative era in transportation, reshaping the landscape of mobility through cutting-edge technologies. Central to this evolution is the integration of artificial intelligence (AI), propelling veh...
Artificial Intelligence (AI)-enabled systems are now increasingly deployed across safety-critical, mission-critical, and socio-technical domains. Existing engineering disciplines offer mature approaches to human and software assurance; however, AI-en...
Manned–unmanned teaming (MUMT) represents a critical evolution in collaborative operations across domains including search and rescue, firefighting, surveillance, and defense. Despite widespread interest in MUMT capabilities, the field lacks a...
Machine learning is increasingly used for spacecraft telemetry monitoring, fault diagnosis, health assessment, mission planning, visual navigation, and execution review. In space missions, explainability is a foundation of trustworthy artificial inte...
Given that the origin of the “robot” comes from efforts to create a worker to help people, there has been relatively little research on making a robot for non-work purposes. However, some researchers have explored robotic arts since Leonardo da Vinci...
Vessel maintenance requires periodic visual inspection of the hull in order to detect typical defective situations of steel structures such as, among others, coating breakdown and corrosion. These inspections are typically performed by well-trained s...
The phenomenon of sustainability, which has been identified in the context of prominence over the past century, has the potential to significantly influence education and its components, as it has been successfully established in other areas of human...
Unmanned aerial vehicles (UAVs) are progressively evolving from remotely operated platforms into intelligent autonomous systems. This research addresses the role of Artificial Intelligence (AI) in advancing UAV capabilities and expanding their applic...
This chapter offers a conceptual and philosophical analysis of the ontological, epistemological, and ethical issues associated with the design, development, and use of Agentic AI in moral and legal decision-making. Its aim is to map, classify, and br...
For the science of autonomous human–machine systems, traditional causal-time interpretations of reality in known contexts are sufficient for rational decisions and actions to be taken, but not for uncertain or dynamic contexts, nor for building...
This paper addresses the challenge of embedded computing resources required by future autonomous Unmanned Aircraft Systems (UAS). Based on an analysis of the required onboard functions that will lead to higher levels of autonomy, we look at most comm...
This paper presents a framework that tackles the challenges met in the development of automation systems featuring collaborative robotics and other machines that have some degree of autonomy. These machines rely on online algorithms for both sensing...
With the rapid advancement of digital technologies, smart construction has emerged as a transformative approach within the construction industry. Central to the success of human-machine collaboration is human-machine trust, which plays a critical rol...
Within a few decades autonomous robotic devices, computing machines, autonomous cars, drones and alike will be among us in numbers, forms and roles unimaginable only 20 or 30 years ago. How can we be sure that those machines will not under any circum...
In the forthcoming era of fully autonomous mining, spanning from drilling operations to port logistics, novel approaches will be essential to pre-empt hazardous situations in the absence of human intervention. The progression towards complete autonom...
Since the Middle Ages, human-powered tools and machines have played an important role in societies. Prominent among these are pedal-powered machines, which harness the overall power from the strongest muscles in the human body. The article identifies...
Our aesthetic experiences are today conditioned by machines, which operate at multiple levels: at the moment of conception of a work, at the moment of conservation and distribution of the work, and at the moment of its contemplation. For art today, i...
Supervising tactile-first robotic traversal in confined, uncertain spaces poses a challenge: operators must be able to intervene without continuous micromanagement. We present a human–machine interface (HMI) that blends operator commands with s...
As humanity grapples with the concept of autonomy for human–machine teams (A-HMTs), unresolved is the necessity for the control of autonomy that instills trust. For non-autonomous systems in states with a high degree of certainty, rational appr...
Supernumerary Robotic Limbs (SRLs) are designed to collaborate with the wearer, enhancing operational capabilities. When human limbs are occupied with primary tasks, controlling SRLs flexibly and naturally becomes a challenge. Existing methods such a...
To support doubly fed wind turbine (DFWT) groups in offshore wind farms, this paper proposes a distributed coordinated control based on the Hamiltonian energy theory. This strategy provides global stability to closed-loop systems and facilitates outp...
This work proposes a novel concept for an intelligent and semi-autonomous human-cyber-physical system (HCPS) to operate future wind turbines in the context of Industry 5.0 technologies. The exponential increase in the complexity of next-generation wi...
Autonomous combine harvesters may improve harvesting timeliness, reduce labor dependence, and support data-driven grain production, but deployment depends on whether they can complete harvesting missions reliably under variable soil–crop–machine inte...
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