Advanced Design of Soft Robots with Artificial Intelligence

In recent years,breakthrough has been made in the field of artificial intelligence(AI),which has also revolutionized the industry of robotics.Soft robots featured with high-level safety,less weight,lower power consumption have always been one of the research hotspots.Recently,multifunctional sensors for perception of soft robotics have been rapidly developed,while more algorithms and models of machine learning with high accuracy have been optimized and proposed.Designs of soft robots with AI have also been advanced ranging from multimodal sensing,human-machine interaction to effective actuation in robotic systems.Nonethe-less,comprehensive reviews concerning the new developments and strategies for the ingenious design of the soft robotic systems equipped with AI are rare.Here,the new development is systematically reviewed in the field of soft robots with AI.First,background and mechanisms of soft robotic systems are briefed,after which development focused on how to endow the soft robots with AI,including the aspects of feeling,thought and reaction,is illustrated.Next,applications of soft robots with AI are systematically summarized and discussed together with advanced strategies proposed for performance enhancement.Design thoughts for future intelligent soft robotics are pointed out.Finally,some perspectives are put forward.

A Review of the Application of Artificial Intelligence in Orthopedic Diseases

In recent years,Artificial Intelligence(AI)has revolutionized people’s lives.AI has long made breakthrough progress in the field of surgery.However,the research on the application of AI in orthopedics is still in the exploratory stage.The paper first introduces the background of AI and orthopedic diseases,addresses the shortcomings of traditional methods in the detection of fractures and orthopedic diseases,draws out the advantages of deep learning and machine learning in image detection,and reviews the latest results of deep learning and machine learning applied to orthopedic image detection in recent years,describing the contributions,strengths and weaknesses,and the direction of the future improvements that can be made in each study.Next,the paper also introduces the difficulties of traditional orthopedic surgery and the roles played by AI in preoperative,intraoperative,and postoperative orthopedic surgery,scientifically discussing the advantages and prospects of AI in orthopedic surgery.Finally,the article discusses the limitations of current research and technology in clinical applications,proposes solutions to the problems,and summarizes and outlines possible future research directions.The main objective of this review is to inform future research and development of AI in orthopedics.

Technologies Supporting Artificial Intelligence and Robotics Application Development

Artificial intelligence(AI)and robotics have gone through three generations of development,from Turing test,logic theory machine,to expert system and self-driving car.In the third-generation today,AI and robotics have collaboratively been used in many areas in our society,including industry,business,manufacture,research,and education.There are many challenging problems in developing AI and robotics applications.We launch this new Journal of Artificial Intelligence and Technology to facilitate the exchange of the latest research and practice in AI and technologies.In this inaugural issue,we first introduce a few key technologies and platforms supporting the third-generation AI and robotics application development based on stacks of technologies and platforms.We present examples of such development environments created by both industry and academia.We also selected eight papers in the related areas to celebrate the foundation of this journal.

Research and Application of Artificial Intelligence in Electric Guitar Performance

The article explores the application of artificial intelligence technology in electric guitar playing.It delves into the advantages of artificial intelligence and its seamless integration into electric guitar performance.Additionally,it investigates the application of artificial intelligence technology through an intelligent playing robot.The research aims to offer substantial support for the advancement of artificial intelligence in electric guitar performance.

Harnessing the Power of Artificial Intelligence in Neuromuscular Disease Rehabilitation: A Comprehensive Review and Algorithmic Approach

Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligence (AI) technology is revolutionizing rehabilitation for individuals with neuromuscular disorders. Through an extensive review, this paper elucidates a wide array of AI-driven interventions spanning robotic-assisted therapy, virtual reality rehabilitation, and intricately tailored machine learning algorithms. The aim is to delve into the nuanced applications of AI, unlocking its transformative potential in optimizing personalized treatment plans for those grappling with the complexities of neuromuscular diseases. By examining the multifaceted intersection of AI and rehabilitation, this paper not only contributes to our understanding of cutting-edge advancements but also envisions a future where technological innovations play a pivotal role in alleviating the challenges posed by neuromuscular diseases. From employing neural-fuzzy adaptive controllers for precise trajectory tracking amidst uncertainties to utilizing machine learning algorithms for recognizing patient motor intentions and adapting training accordingly, this research encompasses a holistic approach towards harnessing AI for enhanced rehabilitation outcomes. By embracing the synergy between AI and rehabilitation, we pave the way for a future where individuals with neuromuscular disorders can access tailored, effective, and technologically-driven interventions to improve their quality of life and functional independence.

Three-dimensional automatic artificial intelligence driven augmented-reality selective biopsy during nerve-sparing robot-assisted radical prostatectomy:A feasibility and accuracy study

Objective:To evaluate the accuracy of our new three-dimensional(3D)automatic augmented reality(AAR)system guided by artificial intelligence in the identification of tumour’s location at the level of the preserved neurovascular bundle(NVB)at the end of the extirpative phase of nerve-sparing robot-assisted radical prostatectomy.Methods:In this prospective study,we enrolled patients with prostate cancer(clinical stages cT1ce3,cN0,and cM0)with a positive index lesion at target biopsy,suspicious for capsular contact or extracapsular extension at preoperative multiparametric magnetic resonance imaging.Patients underwent robot-assisted radical prostatectomy at San Luigi Gonzaga Hospital(Orbassano,Turin,Italy),from December 2020 to December 2021.At the end of extirpative phase,thanks to our new AAR artificial intelligence driven system,the virtual prostate 3D model allowed to identify the tumour’s location at the level of the preserved NVB and to perform a selective excisional biopsy,sparing the remaining portion of the bundle.Perioperative and postoperative data were evaluated,especially focusing on the positive surgical margin(PSM)rates,potency,continence recovery,and biochemical recurrence.Results:Thirty-four patients were enrolled.In 15(44.1%)cases,the target lesion was in contact with the prostatic capsule at multiparametric magnetic resonance imaging(Wheeler grade L2)while in 19(55.9%)cases extracapsular extension was detected(Wheeler grade L3).3D AAR guided biopsies were negative in all pathological tumour stage 2(pT2)patients while they revealed the presence of cancer in 14 cases in the pT3 cohort(14/16;87.5%).PSM rates were 0%and 7.1%in the pathological stages pT2 and pT3(<3 mm,Gleason score 3),respectively.Conclusion:With the proposed 3D AAR system,it is possible to correctly identify the lesion’s location on the NVB in 87.5%of pT3 patients and perform a 3D-guided tailored nerve-sparing even in locally advanced diseases,without compromising the oncological safety in terms of PSM rates.

A new hybrid method with data‑characteristic‑driven analysis for artificial intelligence and robotics index return forecasting

Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability,and the development of the artificial intelligence industry.To provide investors with a more reliable reference in terms of artificial intelligence index investment,this paper selects the NASDAQ CTA Artificial Intelligence and Robotics(AIRO)Index as the research target,and proposes innovative hybrid methods to forecast returns by considering its multiple structural characteristics.Specifically,this paper uses the ensemble empirical mode decomposition(EEMD)method and the modified iterative cumulative sum of squares(ICSS)algorithm to decompose the index returns and identify the structural breakpoints.Furthermore,it combines the least-square support vector machine approach with the particle swarm optimization method(PSO-LSSVM)and the generalized autoregressive conditional heteroskedasticity(GARCH)type models to construct innovative hybrid forecasting methods.On the one hand,the empirical results indicate that the AIRO index returns have complex structural characteristics,and present time-varying and nonlinear characteristics with high complexity and mutability;on the other hand,the newly proposed hybrid forecasting method(i.e.,the EEMD-PSO-LSSVM-ICSS-GARCH models)which considers these complex structural characteristics,can yield the optimal forecasting performance for the AIRO index returns.

A review of medical artificial intelligence

Since the concept of“artificial intelligence”was introduced in 1956,it has led to numerous technological innovations in human medicine and completely changed the traditional model of medicine.In this study,we mainly explain the application of artificial intelligence in various fields of medicine from four aspects:machine learning,intelligent robot,image recognition technology,and expert system.In addition,we discuss the existing problems and future trends in these areas.In recent years,through the development of globalization,various research institutions around the world has conducted a number of researches on this subject.Therefore,medical artificial intelligence has attained significant breakthroughs and will demonstrate wide development prospection in the future.

Smart gas sensor arrays powered by artificial intelligence

Mobile robots behaving as humans should possess multifunctional flexible sensing systems including vision,hearing,touch,smell,and taste.A gas sensor array(GSA),also known as electronic nose,is a possible solution for a robotic olfactory system that can detect and discriminate a wide variety of gas molecules.Artificial intelligence(AI)applied to an electronic nose involves a diverse set of machine learning algorithms which can generate a smell print by analyzing the signal pattern from the GSA.A combination of GSA and AI algorithms can empower intelligent robots with great capabilities in many areas such as environmental monitoring,gas leakage detection,food and beverage production and storage,and especially disease diagnosis through detection of different types and concentrations of target gases with the advantages of portability,low-powerconsumption and ease-of-operation.It is exciting to envisage robots equipped with a"nose"acting as family doctor who will guard every family member's health and keep their home safe.In this review,we give a summary of the state-of the-art research progress in the fabrication techniques for GSAs and typical algorithms employed in artificial olfactory systems,exploring their potential applications in disease diagnosis,environmental monitoring,and explosive detection.We also discuss the key limitations of gas sensor units and their possible solutions.Finally,we present the outlook of GSAs over the horizon of smart homes and cities.

Application of artificial intelligence for the diagnosis,treatment,and prognosis of pancreatic cancer

Pancreatic cancer is a complex cancer of the digestive tract.Diagnosis and treatment can be very difficult because of unclear early symptoms,the deep anatomical location of cancer tissues,and the high degree of cancer cell invasion.The prognosis is extremely poor;the 5-year survival rate of patients with pancreatic cancer is less than 1%.Artificial intelligence(AI)has great potential for application in the medical field.In addition to AI-based applications,such as disease data processing,imaging,and pathological image recognition,robotic surgery has revolutionized surgical procedures.To better understand the current role of AI in pancreatic cancer and predict future development trends,this article comprehensively reports the application of AI to the diagnosis,treatment,and prognosis of pancreatic cancer.

Systematic Survey on Big Data Analytics and Artificial Intelligence for COVID-19 Containment

Artificial Intelligence(AI)has gained popularity for the containment of COVID-19 pandemic applications.Several AI techniques provide efficient mechanisms for handling pandemic situations.AI methods,protocols,data sets,and various validation mechanisms empower the users towards proper decision-making and procedures to handle the situation.Despite so many tools,there still exist conditions in which AI must go a long way.To increase the adaptability and potential of these techniques,a combination of AI and Bigdata is currently gaining popularity.This paper surveys and analyzes the methods within the various computational paradigms used by different researchers and national governments,such as China and South Korea,to fight against this pandemic.The process of vaccine development requires multiple medical experiments.This process requires analyzing datasets from different parts of the world.Deep learning and the Internet of Things(IoT)revolutionized the field of disease diagnosis and disease prediction.The accurate observations from different datasets across the world empowered the process of drug development and drug repurposing.To overcome the issues generated by the pandemic,using such sophisticated computing paradigms such as AI,Machine Learning(ML),deep learning,Robotics and Bigdata is essential.

Humanoid Robots That Behave, Speak, and Think Like Humans:A Reduction to Practice RRC-Humanoid Robot

A radical new approach is presented to programming human-like levels of Artificial Intelligence (AI) into a humanoid robot equipped with a verbal-phoneme sound generator. The system shares 3 important characteristics with human-like input data and processing: 1) The raw data and preliminary processing of the raw data are human-like. 2) All the data are subjective, that is related and correlated with a robotic self-identity coordinate frame. 3) All the data are programmed behaviorally into the system. A multi-tasking Relational Robotic Controller (RRC)-Humanoid Robot, described and published in the peer-reviewed literature, has been specifically designed to fulfill those 3 characteristics. A RRC-controlled system may be behaviorally programmed to achieve human-like high I.Q. levels of subjective AI for the visual signals and the declarative-verbal words and sentences heard by the robot. A proof of concept RRC-Humanoid Robot is under development and present status is presented at the end of the paper.

Automated robot and artificial intelligence-powered wastewater surveillance for proactive mpox outbreak prediction

In the wake of the largest‐ever recorded outbreak of mpox in terms of magnitude and geographical spread in human history since May 2022,we innovatively developed an automated online sewage virus enrichment and concentration robot for disease tracking.Coupled with an artificial intelligence(AI)model,our research aims to estimate mpox cases based on the concentration of the monkeypox virus(MPXV)in wastewater.Our research has revealed a compelling link between the levels of MPXV in wastewater and the number of clinically confirmed mpox infections,a finding that is reinforced by the ability of our AI prediction model to forecast cases with remarkable precision,capturing 87%of the data’s variability.However,it is worth noting that this high precision in predictions may be related to the relatively high frequency of data acquisition and the relatively non‐mobile isolated environment of the hospital itself.In conclusion,this study represents a significant step forward in our ability to track and respond to mpox outbreaks.It has the potential to revolutionize public health surveillance by utilizing innovative technologies for disease surveillance and prediction。

Artificial intelligence and robotics in regional anesthesia

Artificial intelligence(AI)technology is vital for practitioners to incorporate AI and robotics in day-to-day regional anesthesia practice.Recent literature is encouraging on its applications in regional anesthesia,but the data are limited.AI can help us identify and guide the needle tip precisely to the location.This may help us reduce the time,improve precision,and reduce the associated side effects of improper distribution of drugs.In this article,we discuss the potential roles of AI and robotics in regional anesthesia.

A review: Challenges and opportunities for artificial intelligence and robotics in the offshore wind sector

The UK has set plans to increase offshore wind capacity from 22GW to 154GW by 2030. With such tremendous growth, the sector is now looking to Robotics and Artificial Intelligence (RAI) in order to tackle lifecycle service barriers as to support sustainable and profitable offshore wind energy production. Today, RAI applications are predominately being used to support short term objectives in operation and maintenance. However, moving forward, RAI has the potential to play a critical role throughout the full lifecycle of offshore wind infrastructure, from surveying, planning, design, logistics, operational support, training and decommissioning. This paper presents one of the first systematic reviews of RAI for the offshore renewable energy sector. The state-of-the-art in RAI is analyzed with respect to offshore energy requirements, from both industry and academia, in terms of current and future requirements. Our review also includes a detailed evaluation of investment, regulation and skills development required to support the adoption of RAI. The key trends identified through a detailed analysis of patent and academic publication databases provide insights to barriers such as certification of autonomous platforms for safety compliance and reliability, the need for digital architectures for scalability in autonomous fleets, adaptive mission planning for resilient resident operations and optimization of human machine interaction for trusted partnerships between people and autonomous assistants. Our study concludes with identification of technological priorities and outlines their integration into a new ‘symbiotic digital architecture’ to deliver the future of offshore wind farm lifecycle management.

Applying project‐based learning in artificial intelligence and marine discipline:An evaluation study on a robotic sailboat platform

intelligence is penetrating various fields.The demand for interdisciplinary talent is increasingly important,while interdisciplinary educational activities for high school students are lagging behind.Project‐based learning(PBL)in artificial intelligence(AI)and robotic education activities supported by a robotic sailboat platform,the sailboat test arena(STAr),has been shown to popularise AI and robotic knowledge in young students.In the implementation of the programme,PBL was provided for students,and gamification pedagogy was applied to increase participants'learning motivation and engagement.The results show that the proposed STAr‐based programme is capable of delivering the desired knowledge and skills to students at high school levels.The assessment results suggest that most students achieve learning outcomes on average.Students showed more interest in AI and marine disciplines and were willing to participate in more such educational programs.The findings fill the research gap that few existing education platforms have facilitated the teaching and learning of AI and marine disciplines for high school students.

Artificial Intelligence in Healthcare and Medicine:Promises,Ethical Challenges and Governance

Artificial intelligence (AI) is rapidly being applied to a wide range of fields,including medicine,and has been considered as an approach that may augment or substitute human professionals in primary healthcare.However,AI also raises several challenges and ethical concerns.In this article,the author investigates and discusses three aspects of AI in medicine and healthcare:the application and promises of AI,special ethical concerns pertaining to AI in some frontier fields,and suggestive ethical governance systems.Despite great potentials of frontier AI research and development in the field of medical care,the ethical challenges induced by its applications has put forward new requirements for governance.To ensure “trustworthy” AI applications in healthcare and medicine,the creation of an ethical global governance framework and system as well as special guidelines for frontier AI applications in medicine are suggested.The most important aspects include the roles of governments in ethical auditing and the responsibilities of stakeholders in the ethical governance system.

Application of artificial intelligence in surgery

Artificial intelligence(AI)is gradually changing the practice of surgery with technological advancements in imaging,navigation,and robotic intervention.In this article,we review the recent successful and influential applications of AI in surgery from preoperative planning and intraoperative guidance to its integration into surgical robots.We conclude this review by summarizing the current state,emerging trends,and major challenges in the future development of AI in surgery.

Current Situation and Development of Intelligence Robots

Industrial intelligent robots are treated as a measure of na- tional scientific level and technology innovation, and also the important symbol of high-level manufacturing, while service intelligent robots can directly affect people＇ s daily lives. The development of artificial robots in different areas is at- tracting much attention around the world. This article re- views the current situation and development of Chinese and international intelligent robot markets including industrial ro- bots and service robots. The intelligent robot technology and the classification of robots are also discussed. Finally, appli- cations of intelligent robots in various fields are concluded and the development trends and outlook of intelligent robots are explored.