Artificial Intelligence Robotics Research Articles

AI-enhanced subsea maintenance for improved safety and efficiency: Exploring strategic approaches

As the oil and gas industry increasingly explores deeper and more remote offshore sites, the maintenance of subsea infrastructure becomes paramount. The use of Artificial Intelligence (AI) in subsea maintenance offers promising solutions to enhance safety and efficiency in these challenging environments. This review explores strategic approaches to integrating AI into subsea maintenance operations. AI facilitates predictive maintenance by analyzing vast amounts of data collected from sensors and historical maintenance records. Machine learning algorithms can detect patterns and predict equipment failures before they occur, enabling proactive maintenance scheduling. This predictive capability reduces downtime and minimizes the risk of accidents by addressing potential issues before they escalate. AI-enabled autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs) play a crucial role in subsea inspections and repairs. These AI-enhanced robots can navigate complex subsea environments, perform inspections, and execute maintenance tasks with greater precision and efficiency than human divers. By reducing the need for human intervention in hazardous environments, AI-driven AUVs and ROVs significantly improve safety. Furthermore, AI algorithms can optimize maintenance schedules based on factors such as equipment condition, environmental conditions, and operational requirements. By dynamically adjusting maintenance plans, operators can maximize equipment uptime while minimizing costs and risks. This proactive approach ensures that maintenance activities are conducted at the most opportune times, reducing the likelihood of unplanned downtime and improving overall efficiency. Moreover, AI facilitates condition-based maintenance strategies, where equipment health is continuously monitored in real-time. Sensors installed on subsea infrastructure collect data on factors such as temperature, pressure, and vibration, which is then analyzed by AI algorithms to assess equipment condition. By detecting early signs of degradation or malfunction, AI enables timely interventions, preventing costly breakdowns and ensuring optimal performance. In addition to predictive and condition-based maintenance, AI-driven analytics offer insights into operational performance and asset integrity. By analyzing data from various sources, including sensors, historical records, and operational logs, AI can identify trends, anomalies, and optimization opportunities. These insights enable operators to make data-driven decisions that enhance overall system reliability and efficiency. Strategic approaches to implementing AI in subsea maintenance require collaboration between technology providers, operators, and regulatory bodies. Establishing industry standards and guidelines for AI applications in subsea operations is crucial to ensure safety, reliability, and interoperability. Furthermore, investing in research and development to enhance AI algorithms and robotics technology is essential to unlock the full potential of AI in subsea maintenance. AI-enhanced subsea maintenance offers significant benefits in terms of safety and efficiency. By leveraging predictive analytics, autonomous robotics, and real-time monitoring, operators can optimize maintenance activities, reduce downtime, and minimize risks. Strategic approaches to integrating AI into subsea operations require collaboration, investment, and a commitment to advancing technology to meet the challenges of offshore environments.

MoS2/ZnO-heterostructured optoelectronic synapse for multiwavelength optical information-based sensing, memory, and processing

The rapid development of artificial intelligence and humanoid robots requires hardware-level revolution of synapses-based bionic vision system. However, current optoelectronic synapses featuring multiwavelength sensing and multifunctional processing necessitate intricate integrations of multi-materials and floating gate configurations, which induces complex fabrication process and limited integration density. Here, we propose a novel two-terminal optoelectronic synaptic device based on MoS2/ZnO heterostructure which integrates sense and memory functions and realizes multifunctional optical information processing while circumvents the need of complex configurations. By simultaneously exploiting the photo-adsorption oxygen dissociation property of ZnO and the persistent photoconductivity effect of MoS2, the device demonstrates synaptic capability of four-color perception with a single synaptic event consuming a mere 2.55×10−9 J. Different from the traditional power-density sensitive nociceptor, for the first time photon energy-sensitive nociceptors is developed, which can mimic the process of UV irradiation to the retina leading to fear of visible light. Diverse information processing ability, such as photonic information encryption, associative learning, and logic calculation, was demonstrated in a single device, indicating a practical strategy for facile design for future high integration intensity neuromorphic devices.

Human-like intelligent automatic treatment planning of head and neck cancer radiation therapy.

Automatic treatment planning of radiation therapy (RT) is desired to ensure plan quality, improve planning efficiency, and reduce human errors. We have proposed an Intelligent Automatic Treatment Planning framework with a virtual treatment planner (VTP), an artificial intelligence robot built using deep reinforcement learning (DRL), autonomously operating a treatment planning system (TPS). This study extends our previous successes in relatively simple prostate cancer RT planning to head-and-neck (H&N) cancer, a more challenging context even for human planners due to multiple prescription levels, proximity of targets to critical organs, and tight dosimetric constraints.

We integrated VTP with a real clinical TPS to establish a fully automated planning workflow guided by VTP. This integration allowed direct model training and evaluation using the clinical TPS. We designed the VTP network structure to approach the decision-making process in RT planning in a hierarchical manner that mirrors human planners. The VTP network was trained via the Q-learning framework. To assess the effectiveness of VTP, we conducted a prospective evaluation in the 2023 Planning Challenge organized by the American Association of Medical Dosimetrists (AAMD). We extended our evaluation to include 20 clinical H&N cancer patients, comparing the plans generated by VTP against their clinical plans.

In the prospective evaluation for the AAMD Planning Challenge, VTP achieved a plan score of 139.08 in the initial phase evaluating plan quality, and 15 min of planning time with the first place ranking in the adaptive phase competing for planning efficiency while meeting all plan quality requirements. For clinical cases, VTP-generated plans achieved an average VTP score of 125.33±11.12, which outperformed the corresponding clinical plans with an average score of117.76±13.56.

We successfully integrated VTP with the clinical TPS to achieve a fully automated treatment planning workflow. The compelling performance of VTP demonstrated its potential in automating H&N RT planning.

A Solvent-Templated Porous Liquid Crystal Elastomer with Tactile Sensation beyond Reversible Actuation toward Versatile Artificial Muscles.

Liquid crystal elastomers (LCEs), as a classical two-way shape-memory material, are good candidates for developing artificial muscles that mimic the contraction, expansion, or rotational behavior of natural muscles. However, biomimicry is currently focused more on the actuation functions of natural muscles dominated by muscle fibers, whereas the tactile sensing functions that are dominated by neuronal receptors and synapses have not been well captured. Very few studies have reported the sensing concept for LCEs, but the signals were still donated by macroscopic actuation, that is, variations in angle or length. Herein, we develop a conductive porous LCE (CPLCE) using a solvent (dimethyl sulfoxide (DMSO))-templated photo-cross-linking strategy, followed by carbon nanotube (CNT) incorporation. The CPLCE has excellent reversible contraction/elongation behavior in a manner similar to the actuation functions of skeletal muscles. Moreover, the CPLCE shows excellent pressure-sensing performance by providing real-time electrical signals and is capable of microtouch sensing, which is very similar to natural tactile sensing. Furthermore, macroscopic actuation and tactile sensation can be integrated into a single system. Proof-of-concept studies reveal that the CPLCE-based artificial muscle is sensitive to external touch while maintaining its excellent actuation performance. The CPLCE with tactile sensation beyond reversible actuation is expected to benefit the development of versatile artificial muscles and intelligent robots.

Application of new features based on artificial intelligent robot technology in medium-scale urban design pedigree and intelligent management and control

Since the 21st century, China has been vigorously developing urban construction, and now the rise of artificial intelligence (AI) has brought new opportunities for urban design and management. Meso-scale cities are the most developed cities in China and play an important role in economic and social development. The current robot technology is mainly divided into industrial robots and service robots, which can play an important role in the development of cities. This paper aims to apply AI robotics technology to the analysis and intelligent management of mesoscale urban design genealogy. Firstly, the development pedigree of the mesoscale city was analyzed, from which the characteristics of previous designs could be clearly understood. Then, the urban management and control system is intelligently designed from many aspects, the characteristics of the robot are analyzed, and the application of the intelligent robot in urban design is introduced. After that, four developing meso‑scale cities in a province were selected as the evaluation objects, and an Analytic Hierarchy Process (AHP) was proposed to evaluate the application effect of robotics technology in meso‑scale cities. The results showed that the overall score of the robot in urban traffic design was greater than 70 points, and the overall score of urban architectural design was greater than 65 points, which was in the acceptable range. In the application score of urban environment design, the influence was about 70 to 80 points, and the aesthetics was more than 75 points. The cultural aspect of the design impact score was no more than 75 points, while the cultural support aspect score was around 80 points. After the weight calculation, the final overall score was 489 points, and the comprehensive average score was 36 points. The overall composite score and average score were both good. This showed that the application of robot technology to the pedigree analysis and intelligent management and control of mesoscale urban design could achieve good results.

인공지능(AI)시대의 호모 사케르(Homo Sacer)

This study examines the evolution of posthumans in novels and movies as a relationship between sex and love, focusing on Giorgio Agamben's Homo Sacer. Agamben tried to reveal the essence of life politics through the concept of Homo Sacer, which is, bare life. Bare life means only biological life in all living things that Aristotle divided into Zoe and Bios, and humans pursue the life of Bios, who live as a member of a community of society, politics, and culture beyond the life of Zoe. Artificial intelligence robots have only Zoe's life, deprived of their social and political life, Bios. With the development of technology, such AI has a more human appearance, emotion, intelligence, and ability than humans, and dreams of the realm of Bios pursued by humans. I analyzed the emotions and identity of humans and posthuman beings in the AI era, focusing on Rachel in Phillip Dick's novel, the movie Ex Machina's Ava, and David Mitchell's novel of the same name, Cloud Atlas' Sonmi-451. Female mechanical humans are creatures that have life but have no value for existence, and they become invisible others in oppression and governance, appearing as unfamiliar fears, that is, the uncanny. This study examined why humans pursue sexual relationships with machine humans through female AI's uncanny, whether it is possible to fall in love with them, and what it means for programmed AI to evolve on its own, control emotions, and use it to mock humans. As machines become more human-like, their uncanniness makes humans even more uneasy and fearful. If humans can no longer be distinguished from machines, it is necessary to redefine humanity to understand what makes us human. Only then, when the science fiction imagined becomes a scientific reality, can we truly live as humans.

SMART Irrigation Robot

Abstract: Smart irrigation robots are solutions for today's agriculture that solve water management, work efficiency and crop quality problems. This autonomous robotic system combines advanced technology, sensors, artificial intelligence and precision robots to revolutionize the irrigation process. This content highlights the key features and advantages of smart water users. The robot uses a network of soil moisture sensors and weather data to make real-time, data-driven decisions about when and how much to harvest. Using smart algorithms, irrigation strategies can be tailored to specific crop types and growth stages to ensure efficient use. Operating costs. It also promotes sustainability and environmental protection by reducing water waste by providing the required amount of water where and when it is needed.

A STUDY ON ARTIFICIAL INTELLIGENCE IN HR

Artificial Intelligence is rapidly revolutionizing so many industries at such an alarming rate that one such advanced AI robot, Sophia, joined the panel and was pitched questions during the United Nations’s convention on sustainable development. Artificial intelligence is producing multiple solutions for hiring managers including basic recruiting tools, intermediate applications and advanced AI solutions. Together or independently, these tools are creating a more effective way for human resources to predict a candidate’s future success with their company. artificial intelligence (AI) is transforming the human resources field altogether. The current study would throw some light on artificial intelligence breakthroughs and implications with respect to HR . KEYWORDS: Artificial, Intelligence, Human, Resources, Functions, Implications

New Era’s of Artificial Intelligence in Pharmaceutical Industries

Artificial Intelligence (AI) is the future of pharmaceutical industries. We make our tasks easier with help of Artificial Intelligence in future. With help of Artificial Intelligence we can also increase in production in pharmaceutical industry, can be save of dangerous and risky works in the production or manufacturing. Artificial Intelligence can drugs designing in future and discover new drugs and determine the chemical structure of drugs. Artificial Intelligence is very important role play in clinical research. For the pharmacological action drugs are works with the target protein. Than this target proteins are show the pharmacological action and Artificial Intelligence is help in determination of target protein and Artificial Intelligence can easier the drug discovery related work. Artificial Intelligence will used in the marketing such as the patient or customer related information or data collection and deposition. Creation of essential and specialized advertisement for increase product Sell. Different type application will in pharmaceutical industry of Artificial intelligence. And AI will change the pharmaceutical industry or drug associated work and that is come new revolution in pharmacy. Many types AI robots are invented in various pharmacy fields for the help of human being in manufacturing or production in pharmaceutical industry. Artificial Intelligence will advantages and disadvantage for the human beings. This review aims that drug delivery nanosystems design, characterization, and production stand to benefit greatly from artificial intelligence (AI). Furthermore, the ability to perform reverse engineering and ongoing system optimisation is becoming possible with the help of big data.

THE LEGAL CAPACITY (AL-AHLIYYAH) OF ARTIFICIAL INTELLIGENCE FROM AN ISLAMIC JURISPRUDENTIAL PERSPECTIVE

Capacity is the legal right and empowerment of a legal person to individual responsibility. A legal person has the right to social, economic, and political duties and responsibilities in the society to sue and be sued in the law court. However, the issue of artificial persons has been gaining attention in recent times, especially its legal capacity. This paper examines the legal capacity of Artificial Intelligence from Islamic jurisprudential perspective. For instance, legal and juristic issues remain around the legal capacity of humanoids like Sophia Robot which was granted the first full citizenship in Saudi Arabia. Does that citizenship translate to full rights and responsibility like a normal human? The study uses a qualitative method to employ the doctrinal approach of analyzing Islamic jurisprudential opinions on the legal personality of an artificial person. Although there are Islamic thresholds on minors and other interdicted persons, however, the study explores the extent of interpolating classical Islamic rulings of the legal capacity of certain corporations, entities, and interdicted persons on the artificial intelligence robot. The study found that an artificial intelligence robot does not have the complete traits to be considered for natural legal capacity. However, AI has the trait of artificial personality that is justified in Islamic jurisprudence. The vicarious tortious liability can be interpolated on the artificial personality of AI to ensure the protection of the public interest. Therefore, this study lays the groundwork for further studies in understanding how Islamic law can address the rights, responsibilities, and ethical considerations surrounding the use of AI, thereby facilitating the development of comprehensive, and religiously sensitive regulatory frameworks.

Design of robotic arm for the porcelain bushing in substation

With the development and the application popularization of artificial intelligence robot technology and 5G technology, a robotic arm is designed and developed for rinsing porcelain bushing in high voltage substation in this paper. Firstly, the components and implementation of robotic arm are presented, subsequently, a circular cleaning structure with a 120-degree split is proposed to rinse the porcelain bushing. Secondly, a two-stage simple and effective method to realize automatic orientation is proposed utilizing photoelectric switches. Moreover, a prototype of robotic arm with control system is developed based on the regime switching function, and the result of edge computing is transmitted by 5G technology. Finally, feasibility and effectiveness of the robotic arm are verified in the Nanjing power grid. The case study manifests that the robotic arm developed by the proposed method in the paper can achieve efficient rinsing and all the corresponding information can be transmitted preciously. The proposed method lays a foundation for wide application of cleaning robot in high voltage substation.

Advancing infrared display technology with carbon nanotube-embedded spandex fibers

We report on developing a wearable infrared (IR) display based on stretchable conductive fibers fabricated through an expansion–contraction process. The expansion process creates a gap between the strands of spandex fibers. This is achieved by immersing the fibers in a solvent where carbon nanotubes (CNTs) are dispersed, thereby embedding the CNTs. Contraction is achieved through a drying process, which removes the gap between the strands of the spandex fibers. This ensures that the CNTs remain embedded, even after repeated stretching. The CNT-embedded spandex fibers are arranged into a 5 × 7 pixel array. The intensity of the IR rays emitted from the fibers can be controlled by adjusting their temperature, which is achieved by varying the driving voltage. Full-color IR images and displays of letters and numbers are realized through precise control of the IR light intensity. The wearable IR display developed in this study opens up exciting possibilities for integration into advanced systems such as military identification, artificial intelligence robots, autonomous driving, and aerospace industry applications.

Influence of AI: Robotics in Healthcare

The integration of artificial intelligence (AI) and robotics in healthcare has heralded a transformative era, offering unprecedented opportunities to enhance patient care, streamline processes, and augment medical professionals' capabilities. This review article examines the burgeoning influence of AI robotics in healthcare, encompassing various applications, benefits, challenges, and future prospects. We delve into the role of AI robotics across medical diagnosis, surgical interventions, rehabilitation, patient monitoring, and drug discovery. Additionally, we explore the ethical considerations, regulatory frameworks, and societal implications shaping the adoption and advancement of AI robotics in healthcare. By synthesizing current research and real-world implementations, this review elucidates the profound impact of AI robotics, paving the way for a revolutionized healthcare landscape.

A Systematic Approach to Autonomous Agents

Agents and agent-based systems are becoming essential in the development of various fields, such as artificial intelligence, ubiquitous computing, ambient intelligence, autonomous computing, and intelligent robotics. The concept of autonomous agents, inspired by the observed agency in living systems, is also central to current theories on the origin, development, and evolution of life. Therefore, it is crucial to develop an accurate understanding of agents and the concept of agency. This paper begins by discussing the role of agency in natural systems as an inspiration and motivation for agential technologies and then introduces the idea of artificial agents. A systematic approach is presented for the classification of artificial agents. This classification aids in understanding the existing state of the artificial agents and projects their potential future roles in addressing specific types of problems with dedicated agent types.

Can Artificial Intelligence Robots Write Effective Instructions?

The authors analyze the ability of ChatGPT to generate effective instructions for a consequential task: taking a COVID-19 test. They compare the output from a commercial prompt for generating these instructions to those provided by the test manufacturer. They also analyze the input, the prompt itself, to address prompt-engineering issues. The results show that although the output from ChatGPT exhibits certain conventions for documentation, the human-authored instructions from the manufacturer are superior in most ways. The authors conclude that when it comes to creating high-quality, consequential instructions, ChatGPT might be better seen as a collaborator than a competitor with human technical communicators.

The convergence of artificial intelligence and blockchain in industrial robotics

In an era marked by rapid technological advances, understanding the intersection of artificial intelligence (AI), Blockchain, and industrial robotics is both timely and imperative. The research is motivated by the pressing need for a unified framework that stakeholders can refer to as they navigate the complexities of integrating AI and Blockchain into their robotic systems. Through this paper, the aim is to bridge the existing knowledge gap, highlight the synergistic benefits of combining these technologies, and discuss the challenges and opportunities that lie ahead, thereby providing a well-rounded viewpoint crucial for future research and practical applications. This paper serves as a synthesis of existing literature. As AI and Blockchain individually revolutionise various facets of industrial operations, their combined capabilities could bring about unprecedented levels of efficiency, security, and autonomy. The prospect of integration is full of enormous potential, but it also faces some challenges that require sufficient attention. Technological progress, favorable regulatory frameworks, and firm industry adoption are crucial for achieving the expected benefits of such integration.

Artificial cognition vs. artificial intelligence for next-generation autonomous robotic agents.

The trend in industrial/service robotics is to develop robots that can cooperate with people, interacting with them in an autonomous, safe and purposive way. These are the fundamental elements characterizing the fourth and the fifth industrial revolutions (4IR, 5IR): the crucial innovation is the adoption of intelligent technologies that can allow the development of cyber-physical systems, similar if not superior to humans. The common wisdom is that intelligence might be provided by AI (Artificial Intelligence), a claim that is supported more by media coverage and commercial interests than by solid scientific evidence. AI is currently conceived in a quite broad sense, encompassing LLMs and a lot of other things, without any unifying principle, but self-motivating for the success in various areas. The current view of AI robotics mostly follows a purely disembodied approach that is consistent with the old-fashioned, Cartesian mind-body dualism, reflected in the software-hardware distinction inherent to the von Neumann computing architecture. The working hypothesis of this position paper is that the road to the next generation of autonomous robotic agents with cognitive capabilities requires a fully brain-inspired, embodied cognitive approach that avoids the trap of mind-body dualism and aims at the full integration of Bodyware and Cogniware. We name this approach Artificial Cognition (ACo) and ground it in Cognitive Neuroscience. It is specifically focused on proactive knowledge acquisition based on bidirectional human-robot interaction: the practical advantage is to enhance generalization and explainability. Moreover, we believe that a brain-inspired network of interactions is necessary for allowing humans to cooperate with artificial cognitive agents, building a growing level of personal trust and reciprocal accountability: this is clearly missing, although actively sought, in current AI. The ACo approach is a work in progress that can take advantage of a number of research threads, some of them antecedent the early attempts to define AI concepts and methods. In the rest of the paper we will consider some of the building blocks that need to be re-visited in a unitary framework: the principles of developmental robotics, the methods of action representation with prospection capabilities, and the crucial role of social interaction.

Robotics goes PRISMA

Abstract In this article, we review the main results achieved by the research activities carried out at PRISMA Lab of the University of Naples Federico II where, for 35 years, an interdisciplinary team of experts developed robots that are ultimately useful to humans. We summarize the key contributions made in the last decade in the six research areas of dynamic manipulation and locomotion, aerial robotics, human-robot interaction, artificial intelligence and cognitive robotics, industrial robotics, and medical robotics. After a brief overview of each research field, the most significant methodologies and results are reported and discussed, highlighting their cross-disciplinary and translational aspects. Finally, the potential future research directions identified are discussed.

Can an AI-carebot be filial? Reflections from Confucian ethics.

This article discusses the application of artificially intelligent robots within eldercare and explores a series of ethical considerations, including the challenges that AI (Artificial Intelligence) technology poses to traditional Chinese Confucian filial piety. From the perspective of Confucian ethics, the paper argues that robots cannot adequately fulfill duties of care. Due to their detachment from personal relationships and interactions, the "emotions" of AI robots are merely performative reactions in different situations, rather than actual emotional abilities. No matter how "humanized" robots become, it is difficult to establish genuine empathy and a meaningful relationship with them for this reason. Even so, we acknowledge that AI robots are a significant tool in managing the demands of elder care and the growth of care poverty, and as such, we attempt to outline some parameters within which care robotics could be acceptable within a Confucian ethical system. Finally, the paper discusses the social impact and ethical considerations brought on by the interaction between humans and machines. It is observed that the relationship between humans and technology has always had both utopian and dystopian aspects, and robotic elder care is no exception. AI caregiver robots will likely become a part of elder care, and the transformation of these robots from "service providers" to "companions" seems inevitable. In light of this, the application of AI-augmented robotic elder care will also eventually change our understanding of interpersonal relationships and traditional requirements of filial piety.

The Study of Users’ Satisfaction and Acceptance on Artificial Intelligence (AI)

The rise of ChatGPT in recent years has garnered significant attention, prompting widespread interest in the rapid global popularity of this AI technology. Conducting research on this topic would be quite intriguing. The objective of this study was to ascertain the satisfaction and acceptance levels of users of AI robots. This study presents an analysis of the technology acceptance model theory, which enables the prediction of users' intentions and behaviors. The methodology employed in this study involves the utilization of a SWOT analysis framework, which encompasses the identification and evaluation of strengths, weaknesses, opportunities, and threats. The tool has the capability to discern the internal and external factors that impact an organization. The outcome of the investigation will lead to enhancements in the capabilities of ChatGPT, thereby increasing its adoption as a daily tool and enhancing the long-term user experience. This study provides a substantial addition to the field of business, specifically within the domain of artificial intelligence (AI), hence serving as a valuable reference for forthcoming market objectives and strategies.