Artificial Intelligence Robotics Research Articles

The Development Trend of Japan's Aging Population and Its Main Impact on the Economy

In recent years, Japan attracted global attention due to its aging population. This paper analyzes the causes, the process and development trends of aging population in Japan’s society. According to the study, it is not difficult to find that the current aging population in Japan comes from the first baby boom and the aging rate will continue to increase. At the same time, this paper analyzes the main impacts of aging population on economy and finds that although Japan’s aging population may not only lead to economic recession owning to lack of labor, but lead Japanese government to spend more money on overseas trade. However, it will develop nursing industry and artificial intelligence robots specifically for the elderly. The Japanese government try to solve these problems with positive attitude and has introduced many policies. As a result, these efforts to alleviate aging population are worth learning from all over the world.

Hierarchical generative modelling for autonomous robots

Humans generate intricate whole-body motions by planning, executing and combining individual limb movements. We investigated this fundamental aspect of motor control and approached the problem of autonomous task completion by hierarchical generative modelling with multi-level planning, emulating the deep temporal architecture of human motor control. We explored the temporal depth of nested timescales, where successive levels of a forward or generative model unfold, for example, object delivery requires both global planning and local coordination of limb movements. This separation of temporal scales suggests the advantage of hierarchically organizing the global planning and local control of individual limbs. We validated our proposed formulation extensively through physics simulation. Using a hierarchical generative model, we showcase that an embodied artificial intelligence system, a humanoid robot, can autonomously complete a complex task requiring a holistic use of locomotion, manipulation and grasping: the robot adeptly retrieves and transports a box, opens and walks through a door, kicks a football and exhibits robust performance even in the presence of body damage and ground irregularities. Our findings demonstrated the efficacy and feasibility of human-inspired motor control for an embodied artificial intelligence robot, highlighting the viability of the formulized hierarchical architecture for achieving autonomous completion of challenging goal-directed tasks.

Training children with autism spectrum disorder, and children in general with AI robots related to the automatic organization of sentence menus and interaction design evaluation

People with autism spectrum disorder (ASD) have cognitive ability, organizational communication, and self-expression difficulties. It is necessary to study their processing and comprehension of what they hear; their problem-solving, logic, and understanding of cause-and-effect, inference, and the meaning of proverbs; and their ability to ask and answer questions to assess the cognitive stage of their autism. We designed an organizational sentence menu (OSM) to teach children with ASD to communicate with artificial intelligence (AI) robots (operant interaction for auditory understanding, OIAU). Speech generation devices (SGDs) with various OSM designs were tested on four children with autism spectrum disorder, and their improvement was assessed. We used applied behavioral analysis (ABA) to compare the effects of our interventions using various OSM designs. The results showed that our pedagogical guidance strategies were effective. These strategies incorporated AI robot-supported recommendations for the design of interactive operating interfaces that emerge from a stakeholder perspective. This study provides useful information on alternatives that help children with ASD advance their understanding of social interaction.

Consumer-Centric Internet of Medical Things for Cyborg Applications Based on Federated Reinforcement Learning

The Internet of Medical Things (IoMT) is the new digital healthcare application paradigm that offers many healthcare services to users. IoMT-based emerging healthcare applications such as cyborgs, the combination of advanced artificial intelligence (AI) robots, and doctors performing surgical operations remotely from hospitals to patients in their homes. For instance, robot-based knee replacement procedures, and thigh medical care real-time performance monitoring systems are cyborg applications. The paper introduces the multi-agent federated reinforcement learning policy (MFRLP) indicated in mobile and fog agents based on the socket remote procedure call (RPC) paradigm. The goal is to design a consumer-centric cyborg-efficient training testing system that executes the overall application mechanism with minimum delays in the IoMT system. The study develops the RPC based on reinforcement learning and federated learning that adopts dynamic changes in the environment for cyborg applications. As a result, MFRLP minimized the training and testing in the mobile and fog environments by 50%, local processing time by 40%, and processing time by 50% compared to existing machine learning (ML) methods for cyborg applications. The code is publicly available at https://github.com/prayagtiwari/CIoMT

Duty Now and for the Future: Communication, Ethics and Artificial Intelligence

ABSTRACT This essay examines whether and to what extent the “other” in communicative interactions may be otherwise than another human subject and the moral opportunities and challenges this alteration would make available to us. Toward this end, the analysis proceeds in five steps or movements. The first reviews the way the discipline of communication has typically perceived and theorized the role and function of technology. The second and third parts investigate the critical challenges that emerging technology, such as artificial intelligence applications and robots, poses to this standard instrumentalist way of thinking. The fourth part introduces an alternative called “relational ethics,” which effectively flips the script on the usual way of proceeding. And the fifth part presents and responds to one important and notable objection to this alternative. The goal in all of this is not to complicate things but to introduce and formulate a techno-ethics that is more agile in its response to the opportunities and challenges of the 21st century and beyond.

Financing The Development of Artificial Intelligence Maid: An Analysis Of Pertinent Fiqhi Issues

Artificial Intelligence (AI) is the latest machine technology that is replacing the effort of humans and is the fastest-growing sector across the globe. The underlying ethos of AI is to create a secure ecosystem for every human endeavour. Investors are claiming that the invention of an AI assistant such as a robot maid is the future reality. The AI robot is unstoppable and will obstruct how things are done at home. The development of AI and the demand for it indicates a future challenge to domestic activities. Since technology is replacing human efforts, scholars and researchers are concerned about the permissibility of Islamic banks to finance AI projects for the development of robot-maid. A robot maid is likely to exploit gender issues simply because consumers might prefer an AI maid that is male or female. Social violation in the use of AI maid will likely trigger further queries. This study uses the doctrinal approach of the qualitative method to explore Islamic thresholds and analyzes the juristic consideration for financing the development of AI for human development. The study explains the understanding of AI, its contributions to the world economy, and some pertinent issues and challenges. This study found that the growth of AI interventions in homes and care services is a reality, but financing AI maids requires adherence to Islamic requirements, including Shariah compliance and consideration of ethical, economic, security, and social concerns.

가치-태도-행동 모델을 적용한 호텔 AI 로봇서비스에 관한 연구

After COVID-19, hotel industry is rapidly experiencing changes in the business environment, and under the influence of the Fourth Industrial Revolution, hotel industry is striving to secure competitive advantages through differentiation, including the use of big data and the IoT in service provision, as well as the introduction of artificial intelligence(AI) robot services. This study analyzed the perceived value of AI robot services and their impact on usage attitudes and behavioral intentions of customers who have used hotels that have introduced AI robot services.
 The results of the study showed that the value of robot services perceived by customers who have used robot services in hotels is categorized into three dimensions: social, experiential, and functional, and all of them have a positive effect on usage attitudes, with social, functional, and experiential values having a positive effect on usage attitudes in that order.
 Attitude toward use was also analyzed to have a positive effect on behavioral intention, which is consistent with the value-attitude-behavior model. Therefore, it is necessary for hotels to improve the satisfaction of hotel guests through diversified services of AI robot service.

Bioengineering systems «man-machine»: opportunities, challenges and threats

Examples of modern research conducted within the framework of the concept of human improvement with the use of artificial intelligence technologies, genomics, nanotechnology and robotics to improve the functional characteristics of the human body are considered. It is shown that the creation of bioengineering systems «man-machine» can be considered as a supertechnology of the XXI century, which is capable of influencing the entire course of human history, the biosphere, and the process of its development and application may turn out to be a new area of confrontation, the beginning of a «supernova» arms race. In connection with the above, prospective and applied research in this area should be considered in the context of the national security strategy. Along with the work on modeling, creation and application of individual bioengineering systems «man-machine», it is necessary to intensify the development of legal, bioethical and other norms and rules that ensure both technological development (In a given corridor of possibilities) and a high level of safety (by type) of new technologies and developments.

A brief outline of the digitalization of medicine

The article proposes an analysis of modern digital tools in the field of public health. The expediency of improving the experimental legal regime in the field of digital innovations is substantiated. The main reasons for the technological breakthrough in the field of digital innovations in medicine are investigated. An assessment is given of possible options for further technological development of the healthcare sector in the direction of “artificial intelligence”. At the same time, specific mechanisms for the legal regulation of technological solutions introduced into practice are proposed. A special place is given to strategic planning documents that determine and justify, from the point of view of law, the course towards the digital transformation of the healthcare sector. Particular attention is paid to the issue of transition to a new proactive model of medical care using artificial intelligence systems. At the same time, the lack of legal regulation of issues of legal liability in the case of the use of artificial intelligence systems and robotics is taken into account.

Advancements in Agricultural Automation: A Comprehensive Review of Artificial Intelligence and Humanoid Robotics in Farming

This paper discusses about the modern techniques implemented in the field of agriculture which shaped the traditional farming to the smart farming (Agriculture 4.0). The rapid rise in the global population is one among the main reasons, besides monitoring of crops health and yield requires a huge labor force, which is also another reason for promoting intelligent systems into agriculture sector. Conventional farming methods are not suitable to meet this demand, which led robotics to associate with on-field agriculture by means of robot-based technologies like wheeled robots, ground vehicles (manned and unmanned) and aerial vehicles (manned and unmanned) that led to explore the possible advancement in agriculture 3.0. Currently, the evolutionary techniques, such as Artificial Intelligence (AI) and IoT, are implemented in robotic vehicles to make them intelligent systems. Due to unprecedented climatic change and polluted ground water for the past few decades, the crops are being infested with new varieties of diseases. This requires new image processing techniques to classify the diseases based on color, texture and, shape of leaves. The incorporation of image processing technique into AI aids in deciding the appropriate amount of herbicide supplement to the plant based on the prediction of plant growth.

A Study of Ethical Dilemmas and Regulation of AI Chatbots

Chatbots are the product of the development of artificial intelligence to a certain stage, and have different degrees of technical effects under the iteration of technology. Under the development of media technology in recent years, the artificial intelligence robot represented by Chatgpt has attracted widespread attention because of its ability to learn dialogue, and from the current stage of development, there is no doubt that intelligent chatbots have brought about a worldwide revolution in communication technology. It has had a great impact on various fields such as sociology, communication, computation, education, etc. It has produced an underlying reaction to various fields from the technical architecture, changed the previous way of creating, interacting, educating and other behaviours, and has also had an important impact on social construction and interaction. Its unique way of knowledge learning and updating not only brings new possibilities to the network communication ecology, but also brings some ethical dilemmas in communication, which require people to be alert to this new technology and take corresponding preventive and regulatory measures.

Artificial Intelligence Robotics Utilization in Relation to Wellbeing, Burnout and Stress among Operating Room Nurses

Artificial Intelligence Robotics Utilization in Relation to Wellbeing, Burnout and Stress among Operating Room Nurses

Electrospinning Nanofibers as Stretchable Sensors for Wearable Devices.

Wearable devices attract great attention in intelligent medicine, electronic skin, artificial intelligence robots, and so on. However, boundedness of traditional sensors based on rigid materials unconstrained self-multilayer structure assembly and dense substrate in stretchability and permeability limits their applications. The network structure of the elastomeric nanofibers gives them excellent air permeability and stretchability. By introducing metal nanofillers, intrinsic conductive polymers, carbon materials, and other methods to construct conductive paths, stretchable conductors can be effectively prepared by elastomeric nanofibers, showing great potential in the field of flexible sensors. This perspective briefly introduces the representative preparations of conductive thermoplastic polyurethane, nylon, and hydrogel nanofibers by electrospinning and the application of integrated electronic devices in biological signal detection. The main challenge is to unify the stretchability and conductivity of the fiber structure.

작업치료 전문가 활용을 통한 사물인터넷 기반 인공지능 로봇 서비스가 학령기 발달장애 아동 돌봄에 미치는 영향

작업치료 전문가 활용을 통한 사물인터넷 기반 인공지능 로봇 서비스가 학령기 발달장애 아동 돌봄에 미치는 영향

Triphenylamine-Based Helical Polymer for Flexible Memristors.

Flexible nonvolatile memristors have potential applications in wearable devices. In this work, a helical polymer, poly (N, N-diphenylanline isocyanide) (PPIC), was synthesized as the active layer, and flexible electronic devices with an Al/PPIC/ITO architecture were prepared on a polyethylene terephthalate (PET) substrate. The device showed typical nonvolatile rewritable memristor characteristics. The high-molecular-weight helical structure stabilized the active layer under different bending degrees, bending times, and number of bending cycles. The memristor was further employed to simulate the information transmission capability of neural fibers, providing new perspectives for the development of flexible wearable memristors and biomimetic neural synapses. This demonstration highlights the promising possibilities for the advancement of artificial intelligence skin and intelligent flexible robots in the future.

Multifunctional Janus-type self-healing MXene/polyionic liquid flexible sensor

Integration of electronic sensors with signal processing systems is important for artificial intelligence and intelligent robots. It requires mechanically robust, highly sensitive, and self-healing sensing materials that produce recognizable electrical changes in response to external stimuli. Here, we report a multifunctional Janus-type self-healing MXene/polyionic liquid-based flexible membrane for smart sensing. Flexible MXene-NH2@PIL material with self-healing capacity and high tensile properties was constructed by compounding functionalized MXene with polyionic liquid (PIL) with self-healing ability. Deposition of MXene-NH2 resulted in MXene-NH2@PIL with a unique Janus structure that exhibits a variation in the degree of hydrophilicity on both sides and a certain pH response. The material, which can be warmed to over 70 °C in 8 s, also has excellent photothermal conversion. The internal ionic and hydrogen bonding interactions ensure that it can repair damage at 60 °C. The flexible MXene-NH2@PIL sensor prepared from this material can produce significant signal changes in response to small deformations, such as knocks. The flexible MXene-NH2@PIL sensor can also be worn on the finger to detect the bending motion of the finger. This provides an idea for the preparation of self-healing flexible wearable sensors. This study explores the preparation of flexible self-healing sensors by combining the electron-conducting MXene material and ion-conducting PIL.

An Intelligent Robotic System Capable of Sensing and Describing Objects Based on Bimodal, Self‐Powered Flexible Sensors

AbstractThis study presents an intelligent soft robotic system capable of perceiving, describing, and sorting objects based on their physical properties. This work introduces a bimodal self‐powered flexible sensor (BSFS) based on the triboelectric nanogenerator and giant magnetoelastic effect. The BSFS features a simplified structure comprising a magnetoelastic conductive film and a packaged liquid metal coil. The BSFS can precisely detect and distinguish touchless and tactile models, with a response time of 10 ms. By seamlessly integrating the BSFSs into the soft fingers, this study realizes an anthropomorphic soft robotic hand with remarkable multimodal perception capabilities. The touchless signals provide valuable insights into object shape and material composition, while the tactile signals offer precise information regarding surface roughness. Utilizing a convolutional neural network (CNN), this study integrates all sensing information, resulting in an intelligent soft robotic system that accurately describes objects based on their physical properties, including materials, surface roughness, and shapes, with an accuracy rate of up to 97%. This study may lay a robotic foundation for the hardware of the general artificial intelligence with capacities to interpret and interact with the physical world, which also serves as an interface between artificial intelligence and soft robots.

How can artificial intelligence boost firms' exports? evidence from China.

This paper explores the impact of artificial intelligence and industrial robots on firms' export behaviour and divides the impact mechanism into the productivity effect and labour substitution effect. It examines the effect of industrial robots on firms' export value by using Chinese Customs data, Chinese Industrial Firm data and robot data from the International Robot Federation (IRF). The main findings are as follows: Firstly, the impact of artificial intelligence and industrial robots on Chinese firms' export value is generally negative, which means the negative labour substitution effect dominates the positive productivity effect. Secondly, the impact of artificial intelligence varies significantly by industry, and the export value of firms from high-tech industries benefits from the use of industrial robots. Thirdly, the impact of artificial intelligence on firms' export value also varies by time; before 2003, the use of industrial robots showed mainly an inhibiting effect on firms' exports, which turned into a driving effect thereafter, and after 2006, industrial robots began to significantly promote firms' export. Finally, the higher the quality of export products, the more likely the use of industrial robots will be to promote firms' export value, and the higher the capital-labour ratio is, the more likely firms' export value will be to benefit from the use of artificial intelligence and industrial robots. On the basis of these findings, this study proposes promoting the productivity effect to dominate the labour substitution effect through technological progress and the improvement of export product quality.

Views about perceived training needs of health care professionals in relation to socially assistive robots: an international online survey

Background As Artificial Intelligence and social robots are increasingly used in health and social care, it is imperative to explore the training needs of the workforce, factoring in their cultural background. Objectives Explore views on perceived training needs among professionals around the world and how these related to country cultures. Design Cross-sectional, descriptive, mixed-methods international online survey. Methods Descriptive statistical analysis explored the ranking across countries and relationships with three Hofstede cultural dimensions. Thematic analysis was conducted on the open-ended text responses. Results A sample of N = 1284 participants from eighteen countries. Knowing the capabilities of the robots was ranked as the top training need across all participating countries and this was also reflected in the thematic analysis. Participants' culture, expressed through three Hofstede's dimensions, revealed statistically significant ranking differences. Conclusions Future research should further explore other factors such as the level of digital maturity of the workplace. Impact Statement Training needs of health and social care staff to use robotics are fast growing and preparation should factor in patient safety and be based on the principles of person- and culture-centred care.

Deployment of an Artificial Intelligent Robot for Weed Management in Legumes Farmland

This groundbreaking research introduces an AI-based approach for revolutionizing weed management in legume farmland, addressing the limitations of traditional methods and introducing a new era of cost-effective and precise weed detection and removal. Traditional methods of removing weeds from farmland involving machinery or chemicals often resulted in high costs and imprecise outcomes. To address these challenges, an advanced image recognition algorithm was proposed, which harnessed smart machines to minimize costs and environmental risks. By utilizing computer vision technology, weeds were accurately identified and targeted for removal. A machine learning model was trained using relevant datasets to enable precise weed management. The AI-powered robot, equipped with advanced image recognition algorithms, demonstrated exceptional accuracy and speed, performing weed removal and decomposition 1.2 times faster than traditional manual labour. This breakthrough in weed management technology offers farmers a means to optimize crop yields, enhance food production, and minimize the environmental impact associated with chemical herbicides. A prototype of the robot was fabricated and evaluated in real-world farming conditions. Field tests were conducted on a bean farm and it’s demonstrated the robot's exceptional accuracy, with only a 2% deviation from the actual weed quantity. This research showcased the potential of AI-based weed management systems in legume farming, offering cost-effective and precise weed detection and removal. This research sets a precedent for the integration of AI in modern agriculture, driving the industry toward a more environmentally conscious and economically viable future. The AI-based weed management system empowers farmers, ensuring bountiful harvests, increased profitability, and a greener, more sustainable tomorrow while attention should be given to manufacturing this model for industrial and or commercial applications.