Artificial Intelligence Robotics Research Articles

Study on Distributed Consistent Cooperative Control of Multi-ART in Automated Container Terminals

In order to address the congestion problem of vehicles in quay of automated container terminal with parallel layout and side-loading operations, the study regards the terminal operation system as a multi-agent system (MAS), and proposes a dynamic cooperative speed control schema of multi-ART(Artificial Intelligence Robot of Transportation, ) for the purpose of smart and distributed traffic control of container terminals. Via the real-time data interchange and message passing with ART group, the individual ART implements the collaborative speed regulation with the combination of the dynamic speed regulation strategy, so as to adjust the sequence of ARTs arriving at the quay which can decrease the waiting time of ARTs at the quay. Considering the consistency problem of individual and group agent among the dynamic speed regulation of ARTs, a novel distributed consensus protocol is established to assure that the individual status of ART will tend to converge basically during the collaborative speed regulation process, and the convergence of system can be guaranteed. Based on the case of automated container terminal of Tianjin Port, the paper establishes a multi-agent based simulation model, and simulates the decision-making process, and validates the effectiveness of mentioned model and strategy. The results demonstrate that the strategy can decrease the waiting time of ARTs under uncertainty environment of port and improve the operation efficiency of system.

Human rights during the mass introduction of artificial intelligence and robotic systems into public life

Purpose: This article considers legal approaches to implementing human rights during the mass exploitation of artificial intelligence and robotic systems in public life. Methods: Within the framework of this study, an emphasis is placed on the legal regulation of artificial intelligence systems and robotics used for remote biometric identification of a person and the creation of social credit systems. This study analyzes different models of legal regulation that are typical of certain countries and regions, including the UK, USA, China, and the EU. Results: In the UK, it is allowed to use real-time face recognition systems in public spaces but the set of scenarios and situations for their use is significantly limited by legislation and law enforcement. The legal regulation of these systems in each state is based on a constant dialogue between state and civil society. The use of artificial intelligence and robotic systems to create social credit systems is tested in some countries. Modern states have formed several approaches to the creation of such systems: some of them completely prohibit these systems, while others develop a technological and regulatory framework for the creation of national systems.

Recommendatory Solutions for ensuring Fair Use of Artificial Intelligence in present times

This paper is an attempt to find viable solutions to ensure fair use of artificial intelligence technologies and products in the present times so that their usage does not violate the fundamental as well as human rights of the individuals. It is necessary that human rights which are soul and heart of the humans for their survival does not become a subject of abuse in front of artificial intelligence. Therefore, in this research paper, five different solutions have been recommended that can be adopted in order to achieve the goal. The five potential solutions are firstly, providing the status of electronic personhood to Artificial Intelligence Robots, secondly, need for Artificial Intelligence Literacy, thirdly, strong Data Protection Framework, fourthly, ethical Code of Conduct, and fifthly, establishment of Artificial Intelligence Commission.

Conductive and eco-friendly gluten/MXene composite organohydrogels for flexible, adhesive, and low-temperature tolerant epidermal strain sensors

Conductive hydrogels have drawn tremendous attention in the field of artificial intelligence, health monitoring, and soft robotics. However, combining hydrogels with conductivity, self-adhesiveness, low-temperature tolerance, biocompatibility, and biodegradability in green and low-cost ways remains a great challenge. Hence, the conductive MXene nanosheets were introduced into gluten networks by simple cooking inspired processes and solvents exchanged with glycerol/water binary solution to fabricate conductive organohydrogels (GMOHx). The GMOHx were conductive (5 ×10−4 S/m), flexible, adhesive to various surfaces (a max lap-shear strength of ~ 45.9 KPa), low-temperature tolerant (conductive and flexible under −20 °C), biocompatible, and easily degradable (degraded in neutral proteinase dispersion within 2 days), which can be applied as epidermal strain sensors to detect both large (e.g., elbow, wrist, and knee bending) and subtle (e.g., swallowing) scale human motions with accurate and long-term stable signals even under sub-zero temperatures.

An Empirical Analysis of AI Related Scientific Knowledge and Technologies To Support Elderly Independent Living

<p>The constant increase of an aging society unveils social and economic problems. Elderly independent living (EIL) is supported by numerous services and technologies that take care of their emotional and physical health. Previous studies have reviewed the potential of Artificial Intelligence (AI) applications to support health care, such as AI robots and intelligent senior well-being support systems. A growing number of scientists and tech companies are working on AI applications to help the elderly independent living. We propose to identify AI technological innovation opportunities when developing AI solutions to help the elderly independent living. The research consists of two steps: 1) Identifying AI solutions to help elderly independent living by implementing scientometric analysis on scientific publications related to AI technologies and the elderly. 2) The review and national-level comparison of the identified AI solutions under the proposed framework of elderly need, supporting function, underlying technologies and scientific knowledge. Based on an analysis of the literature on emerging technology in the third AI Boom, we pinpoint science mapping to grasp the situation of research and development of emerging technologies in various regions, to explore the status of technological and research cooperation, to find out the hot research topics of AI technologies in dealing with the problem of aging, to discover the direction of technological development and innovation opportunities in the future, and to combine with the actual need of EIL for exploring the innovative potential of AI technology. From our analysis we can argue that solutions to support elderly independent living require the integration of knowledge from various disciplines, services and products such as machine learning, sensors, data analysis, IoT, wearable devices, sociology and healthcare.</p><p><span>Keywords : Artificial Intelligence, Aging society, Elderly independent living, Scientometric, Network analysis</span></p>

Conversational artificial intelligence and affective social robot for monitoring health and well‐being of people with dementia

AbstractBackgroundSocial robots are anthropomorphised platforms developed to interact with humans, using natural language, offering an accessible and intuitive interface suited to diverse cognitive abilities. Social robots can be used to support people with dementia (PwD) and carers in their homes managing medication, hydration, appointments, and evaluating mood, wellbeing, and potentially cognitive decline. Such robots have potential to reduce care burden and prolong independent living, yet translation into PwD use remains insignificant.MethodWe have developed two social robots ‐ a conversational robot and a digital social robot for mobile devices capable of communicating through natural language (powered by Amazon Alexa) and facial expressions that ask PwD daily questions about their health and wellbeing and also provide digital assistant functionality. We record data comprising of PwD’s responses to daily questions, audio speech and text of conversations with Alexa to automatically monitor their health and wellbeing using machine learning. We followed user‐centric development processes by conducting focus groups with 13 carers, 2 PwD and 5 clinicians to iterate the design. We are testing social robot with 3 PwD in their homes for ten weeks.ResultWe received positive feedback on social robot from focus group participants. Ease of use, low maintenance, accessibility, assistance with medication, supporting with health and wellbeing were identified as the key opportunities for social robots. Based on responses to a daily questionnaire, our robots generate a report detailing PwD wellbeing that is automatically sent via email to family members or carers. This information is also stored systematically in a database that can help clinicians monitor their patients remotely. We use natural language processing to analyse conversations and identify topics of interest to PwD such that robot behaviour could be adapted. We process speech using signal processing and machine learning classifiers to identify emotions and mood.ConclusionAffective social robots with voice and facial expressions have a great potential for enhancing dementia care at home. Combining responses to daily questions, topics of conversations and emotions from speech analysis can help assess daily status of PwD automatically and monitor their health and well‐being over time remotely.

Low-Temperature tolerance and conformal adhesion zwitterionic hydrogels as electronic skin for strain and temperature responsiveness

Flexible electronics have been extensively explored for health monitoring, artificial intelligence, and soft robotics. However, it remains challenging to simultaneously achieve temperature and strain monitoring over a wide perception range that are highly analogous to natural human skin. Herein, an intelligent thermosensation zwitterionic hydrogel with superior low-temperature tolerance and conformal adhesion was successfully prepared for strain-temperature dual-modal sensors, based on the temperature-dependent self-association interactions of sulfobetaine methacrylate (SBMA) polymer chains and the incorporation of thermosensitive TEMPO-oxidized cellulose/polyaniline nanofibers (CPA NFs) in glycerol-water binary solvent system. Significantly, the TEMPO-oxidized cellulose acting as the reinforced skeleton guided the in-situ polymerization of polyaniline, while the tunneling current activated by thermal vibration of CPA NFs and the charge transfer caused by the spatial position adjustment collectively contributed to the superimposed signal recognition ability. By leveraging the glycerol molecules to inhibit the ice crystal growth without the compromise of flexibility (1095 %), strain sensitivity (GF = 1.25), and thermal responsiveness (TCR = 2.01% °C−1), the accurate determination paradigm for dual-modal strain and temperature sensor over a wide temperature range (-40–80 °C) was subtlyachieved. Additionally, we corroborated that the conformal adhesion between zwitterionic active sites (e.g. –N+(CH3)3 or -SO3-) and dynamic interfaces was critical for minimizing interface slippage and delamination, as well as maintaining real-time electricalsignal stability. The assembled zwitterionic epidermis sensor array that conformally adhered to fingers could realize the subtle signal identification and localized temperature detection, which presented promising prospects for designing the multi-modal skin-like responsiveness electronic skins that suitable for harsh temperature conditions.

Evaluation of the Postoperative Nursing Effect of Thoracic Surgery Assisted by Artificial Intelligence Robot.

In order to evaluate the postoperative nursing effect of artificial intelligence robot-assisted thoracic surgery, this study proposed the Da Vinci robot-assisted pulmonary lobotomy, from January to December 2014; 42 patients (15 males and 27 females, aged 33–69 years old) underwent lobectomy with the Da Vinci robot system in the chest hospital. A series of postoperative nursing was carried out. The surgical results showed that 42 patients with Da Vinci robot-assisted lobectomy had operation time of 62–225 min and blood loss of 70–300 mL. There was no intraoperative blood transfusion, the intraoperative central rate was maintained at 60–100 times/min, and the blood pressure was maintained at 90–140/60–90 mmHg. No patient was transferred to thoracotomy, and 2 patients were performed robotic wedge resection first, and then, robotic lobectomy was performed after malignant tumor was confirmed by freezing results, with relatively light postoperative pain, no infection, beautiful wound, and smooth recovery and discharge. Robot-assisted lobectomy is a new technique with advantages of less trauma, less pain, faster recovery, and safer and more thorough lymph node dissection.

Brawn with Brains

Abstract There are now many organizations that are utilizing some form of artificial intelligence or machine learning-powered robotics to help with automation capabilities. These companies are learning just how many duties that were once considered too hard for robots these AI-powered machines can handle.

Stretchable Carbon Nanotube Thin-Film Transistor Arrays Realized by a Universal Transferable-Band-Aid Method

Stretchable electronics offer new possibilities for humans and artificial intelligent robots, in which stretchable transistors are the core components. Either geometric engineering or intrinsic material integration has its own limitations for realizing high-performance stretchable transistors. In this work, by combining the advantages of both approaches, we propose a novel transferable-Band-Aid method to realize stretchable carbon nanotube (CNT) thin-film transistor (TFT) arrays with high electrical performance and stretchability simultaneously. This method uses polyimide (PI) tapes to transfer devices to elastomer substrates. The mobility and ON/OFF-current ratio of the stretchable CNT-TFTs reach 24 cm2/ $\text{V}\cdot \text{s}$ and $1.1\times10$ 5, respectively. After stretched by 50% and 100% for 2000 cycles, the device performance is maintained on both polydimethylsiloxane and Eco-flex substrates. Neither obvious degradation on electrical properties nor displacement between the PI and the elastomer is observed during the stretching. The mechanical performance of the stretchable devices has also been verified and analyzed by simulation using ANSYS. Young’s modulus ratio between the stiff island and the elastomer substrate influences stretchability and stress distribution of the devices. The simulation result provides a guideline for realizing highly robust stretchable devices. The Band-Aid structure could generally be stuck to most elastomer substrates, providing a new solution to convert flexible devices into stretchable devices universally. The demonstrations of the design exhibit its excellent transferability, conformal capability, and versatility, showing its application potentials in wearable devices, biological-human interfaces and Internet of Things.

Research on manipulator control based on deep reinforcement learning

With the gradual improvement of the influence of intelligent robots in production and life, it has greatly facilitated people's production and life. Therefore, people's requirements for intelligent robots are also increasing, and are developing towards more humanization and intelligence. However, at present, there are still many imperfections in the field of intelligent robot technology in China. In order to solve the problems in work, we must further strengthen the research on artificial intelligence theory and robot technology. Only in this way can we realize the all-round development of intelligent robot system. So this paper will discuss the deep reinforcement learning in the theory of artificial intelligence, and explain its basic theory, research status, existing problems and future development direction. Moreover, under the background of the overall improvement of the current industrial development level, this paper will also talk about the manipulator widely used in the industrial field and the research status of manipulator control based on deep reinforcement learning, hoping to provide effective help for the development of related fields.

The Application Status and Development Prospects of Artificial Intelligence and Industrial Robots in the Manufacturing Industry

China has achieved quite good results in the research and application of information technology and other fields. The continuous advancement of technologies such as AI, 5G communications, and cloud computing have played a key role in the development of intelligence, convenience, and innovation in various industries in China. The application of AI as a technical means in the Internet industry has been relatively mature and has achieved relatively good results. However, AI has not yet achieved satisfactory results in the development and upgrading of the manufacturing industry. As the most critical industry in the real economy, the manufacturing industry has played a decisive role in the sustainable development of China’s real economy. Therefore, it is necessary to promote the deep integration of AI technology and manufacturing and to further advance the process of intelligent manufacturing. Accordingly, this article discusses the application status and development prospects of AI and industrial robots in the manufacturing industry.

Influence of Vocalized Reading Practice on English Learning and Psychological Problems of Middle School Students.

The purpose of this study is to improve the English learning anxiety and learning effect for middle school students. From the perspective of educational psychology, the influence of vocalized reading practice on the English learning of students is studied based on the self-efficacy theory and the schema theory. To encourage the students to practice English, the study might solve the problem of insufficient opportunities by applying the artificial intelligence (AI) chat system to the oral English practice of the students. Several research hypotheses are put forward, which concern the correlation between the English learning anxiety of the students with their self-efficacy, topic familiarity, and English grades under vocalized reading practice. Then, the hypotheses are verified through a controlled trial and a questionnaire survey (QS). Afterward, the experimental and QS data are statistically analyzed and tested with a regression model. The results show that the English grades, self-efficacy, and topic familiarity of the students have been significantly improved in the experimental group after the vocalized reading practice. The significance coefficient of the regression model is P = 0.000 < 0.05, which can be used to verify the proposed hypotheses. The English grades, self-efficacy, and topic familiarity can well-predict the English learning anxiety of the students. The computer simulation in educational communication (CSIEC) teaching system and AI can help create an interactive learning environment for the students to practice oral English by chatting with AI robots.

Communicative Development and Diffusion of Humanoid AI Robots for the Post-Pandemic Health Care System

As humanoid robot technology, anthropomorphized by artificial intelligence (AI), has rapidly advanced to introduce more human-resembling automated robots that can communicate, interact, and work like humans, we have begun to expect active interactions with Humanoid AI Robots (HAIRs) in the near future. Coupled with the HAIR technology development, the COVID-19 pandemic triggered our interest in using health care robots with many substantial advantages that overcome critical human vulnerabilities against the strong infectious COVID-19 virus. Recognizing the tremendous potential for the active application of HAIRs, this article explores feasible ways to implement HAIRs in health care and patient services and suggests recommendations for strategically developing and diffusing autonomous HAIRs in health care facilities. While discussing the integration of HAIRs into health care, this article points out some important ethical concerns that should be addressed for implementing HAIRs for health care services.

Robert Wise’s The Day the Earth Stood Still (1951) and Interplanetary Emissary Klaatu Are Not Anti-Atomic: A Reassessment of the Filmic Evidence

Inspired by a 1940s short story by Harry Bates, scripted by Edmund H. North, and directed by Robert Wise, The Day the Earth Stood Still (1951) is a science fiction cult classic. Of all its diverse interpretations, a commonly adopted reading influenced by the dawning of the Atomic Age parades it as an anti-nuclear exemplar starring alien emissary Klaatu visiting Earth with his robot companion Gort to (supposedly) suppress humanity’s atomic progress. However, upon a close forensic inspection of the film and commentator comments, this anti-atomic claim is resoundingly rejected. Utilizing humanist film criticism as the guiding analytical lens (i.e., looking inside not outside the frame), plus a selective review of the critical literature, it was demonstrated that: (a) there is a dearth of atomic iconography and dialogue, (b) there is no mention of banning atomic energy or weapons, (c) Earth’s atomics are nascent and not serious threats to the Federation, and (d) Klaatu is not anti-atomic but proudly pro-atomic. Overall, this SF film is strongly pro-nuclear in intention, word, and deed, which was frequently misinterpreted due to faulty film criticism, invented facts, and jumping to conclusions, and thus in need of academic correction. Further research into alien first-contact scenarios, robotic artificial intelligence, and the moral make-up of the SF universe is warranted and long overdue.

Augmented Reality Meets Artificial Intelligence in Robotics: A Systematic Review.

Recently, advancements in computational machinery have facilitated the integration of artificial intelligence (AI) to almost every field and industry. This fast-paced development in AI and sensing technologies have stirred an evolution in the realm of robotics. Concurrently, augmented reality (AR) applications are providing solutions to a myriad of robotics applications, such as demystifying robot motion intent and supporting intuitive control and feedback. In this paper, research papers combining the potentials of AI and AR in robotics over the last decade are presented and systematically reviewed. Four sources for data collection were utilized: Google Scholar, Scopus database, the International Conference on Robotics and Automation 2020 proceedings, and the references and citations of all identified papers. A total of 29 papers were analyzed from two perspectives: a theme-based perspective showcasing the relation between AR and AI, and an application-based analysis highlighting how the robotics application was affected. These two sections are further categorized based on the type of robotics platform and the type of robotics application, respectively. We analyze the work done and highlight some of the prevailing limitations hindering the field. Results also explain how AR and AI can be combined to solve the model-mismatch paradigm by creating a closed feedback loop between the user and the robot. This forms a solid base for increasing the efficiency of the robotic application and enhancing the user’s situational awareness, safety, and acceptance of AI robots. Our findings affirm the promising future for robust integration of AR and AI in numerous robotic applications.

Using Artificial Intelligence (AI)-interfaced robotic toys in early childhood settings: a case for children’s inquiry literacy

ABSTRACT This study explores the use of interactive Artificial Intelligence (AI)-interfaced robotic toys within early childhood (EC) settings to develop children’s inquiry literacy. Arguments about the appropriate role of AI in EC education have received much attention when examining the potential of the integration of technology into children’s play and learning. Using Vygotsky’s mediation theory (1978) and employing a design-based research methodology, teachers intentionally used AI robotic toys to engage children (4–5 years old) during play experiences. The data from both teachers’ and children’s interviews, observations and artefact analysis revealed how children creatively collaborated with their peers to create a sustainable city for their robot and ‘his’ family to live happily. Children’s play with the AI robot fostered inquiry literacies – namely creative inquiry, emotional inquiry and collaborative inquiry. This study contributes to research by exploring the use of AI toys together with physical and artificial environments and offers a case to shape children’s inquiry literacies. Implications lie in upskilling EC teachers to provide opportunities to play with AI-interfaced robotic toys to foster children’s inquiry literacy development process.

Ultra‐Stretchable Self‐Healing Composite Hydrogels as Touch Panel

AbstractDevelopment of ultra‐stretchable and sensitive soft touch panel is of great importance for broad applications in artificial intelligence, wearable devices, and soft robotics. However, traditional human‐computer interfaces (HCIs) suffer from the discomfort and asynchronous signals in current application scenarios. Herein, a hydrogel‐based self‐healing touch panel, which is highly deformable, and both mechanically and electrically self‐healable, has been successfully developed from a poly(N,N′‐dimethylacrylamide)/silica hydrogel which possesses an ultra‐high stretchability &gt;3800%. A surface‐capacitive touch mechanism is adopted to sense a touched position. The panel can be operated under high areal strain without sacrificing its functionalities. Skin touch panel is constructed and adhered to human skin, with the strong performance and self‐healing ability demonstrated by writing words and playing games.

Electro-Blown Spun Silk/Graphene Nanoionotronic Skin for Multifunctional Fire Protection and Alarm.

Artificial protective skins are widely used in artificial intelligence robots, such as humanoid robots, mobile manipulation robots, and automatic probe robots, but their safety in use, especially flame retardancy, is rarely considered. As many artificial skins are designed for use in flammable or even explosive environments, flammability is a significant concern. Herein, a flame-retardant silk/graphene nanoionotronic (SGNI) skin is developed by using a rationally designed high-throughput electro-blown spinning technique, with a more efficient production efficiency than electrospinning. These flame retardant SGNI skins combine the advantages of nanofibrous and ionotronic materials, and they are sustainable, conductive, highly porous, mechanically robust, highly stretchable, self-adhesive, and humidity- and temperature-sensitive. These merits support the assembly of SGNI skins into a fire alarm system, with real-time alarm (response in 2 s) to mobile phones, clouds, and a central control system. The concept that combines a flame retardant and fire alarm material into an intelligent skin may provide potential solutions toward the design of protective skins for robotics and human-machine interactions.

Auditing the Impact of Neuro-Advancements on Health Equity

Health equity understood as the ability to live a healthy life, to have a good life, is impacted by many social determinants and by the social marginalization of various groups. “Measures” that use indicators to cover social determinants of a good life are useful tools to audit the impact of neuro-advancements on health equity. In this scoping review, I covered over 50 neurotechnologies, neuroenhancement, artificial intelligence (AI) machine learning (ML), robotics, neuroethics, neuro-governance and neurotechnology governance and various “measures” that focus on the ability to have a good life to answer three research questions: 1) Are the “measures” engaged with in the academic literature covering health equity or the chosen technologies? 2) Does the academic literature focusing on the technologies covered, neuroethics, or neurotechnology governance engage with health equity? 3) To what extent does the academic literature focusing on the technologies covered engage with the different primary and secondary indicators of four of the “measures” (social determinants of health, Better Life Index, Canadian Index of Well-Being, and community-based rehabilitation matrix)? For the scoping review, I examined the academic literature present in SCOPUS, which includes all Medline articles, and the 70 databases accessible under EBSCO-HOST and I employed a quantitative hit count approach for the analysis. I found that the term “health equity” was only mentioned in conjunction with the terms “determinants of health” and “social determinants of health” in a substantial way. Three of the terms linked to the “measures” were each mentioned in less than 10 abstracts and 16 terms linked to the “measures” were not mentioned at all in conjunction with the term “health equity”. Health equity was also rarely to not at all mentioned in conjunction with the different technologies covered and not at all in conjunction with the terms “neuroethics”, “neurotechnology governance” or “neuro-governance”. Finally, there was uneven engagement with the primary and secondary indicators of the four chosen “measures” in conjunction with the technologies covered. The results reveal vast opportunities at the intersections of neuroethics and neuro-governance and science and technology governance in general, health equity, social justice, and wellbeing discourses. J Neurol Res. 2021;12(2):54-68 doi: https://doi.org/10.14740/jnr695