Robotic Technology Research Articles

Overview of Key Technologies in Surgical Robots and Optimization Discussions

Surgical robot is the national strategic diagnostic and therapeutic equipment research focus, get a number of scientific research institutes, colleges and universities and enterprises pay extensive attention to the design and development of a variety of surgical robots, and registration declaration. This article explores the critical technologies of surgical robots and key areas for optimizing their performance, including kinematic positioning errors, pose errors, feedback model errors, image recognition positioning errors, path planning, and safety aspects. The findings not only provide a scientific basis for future standardization research on surgical robots but also offer significant theoretical and practical references for the research, manufacturing, and registration processes in the medical robotics industry.

Zero-shot autonomous robot manipulation via natural language

Smart manufacturing revolutionizes advanced automation by leveraging deep learning and robotics technology. Nevertheless, deep learning implementation in manufacturing faces several challenges in preparing datasets, training a model, and adapting to various applications. Furthermore, programming languages are required to develop deep learning models and communicate with robots, which is not straightforward to quickly and precisely reflect human intentions in manufacturing processes. To alleviate the issue, this study proposes an autonomous zero-shot robot manipulation framework via natural language. Specifically, the Segmentation Anything Model (SAM), a promptable image segmentation model, first segments objects in images captured by an RGB-D camera, which are passed to Generative Pre-trained Transformers (GPTs), a Large Language Model (LLM), to identify and localize a designated object based on human commands given in natural language. Afterwards, the Robot Operating System (ROS) manipulates a robot to a localized position. With no additional programming or specialized skills in object localization and robot manipulation, the framework demonstrates an autonomous robot automation approach through intuitive communication between humans and machines through natural language.

Research on Visual Recognition of Service Robots Based on YOLO Algorithm

In modern society, based on the aging of population and the rapid development of intelligent technology, the demand for intelligent service robots is increasing, and visual recognition is one of the key technologies of service robots. The rapid development of deep learning technology provides new solutions for visual recognition. Existing target recognition algorithms have the problem of complex model and slow inference speed. According to the above problems, this paper proposes a visual recognition algorithm based on YOLO series, which is used for the visual recognition design scheme of service robot. It can ensure the detection accuracy, reduce the speed of the model complexity, speed up the reasoning, and determine whether to meet the actual needs. Through randomly selected pictures, the results show that the design scheme can effectively improve the detection accuracy and real-time of the service robot on targets, and enhance its autonomous service ability in various complex environments.

Application of artificial intelligence in business management and financial market forecasting

In today's business world, artificial intelligence as a new technology has provided dynamic and flexible capabilities in organizational decision-making processes, considering that organizational decision-making often faces challenges due to the complexity and multiplicity of factors affecting it. The application of artificial intelligence as A powerful tool can be effective in improving the organizational decision-making process and improving the performance of organizational managers. Artificial intelligence is one of the popular and widely used new sciences in almost all aspects of life and can do things faster and more accurately. The numerous advantages of artificial intelligence and its wide applications today are not hidden from anyone. Financial services companies are constantly looking for ways to gain superiority in the capital market and surpass their competitors. To do this, companies are moving away from old systems and models They adopt a more agile business that includes artificial intelligence techniques in capital markets, artificial intelligence in financial markets and machine learning (ML). In capital markets, companies use artificial intelligence and ML projects in coordination with RPA robotic process automation technologies to meet customer requests, speed up financial market analysis, and more accurately identify risk in the business process.

Integrating Robotics for Enhanced Business Operations

This research study delves into the strategic incorporation of robotics into global business operations, stressing the interaction between technological progress and geopolitical and economic factors. Through an analysis of historical events such as the Cold War, the rise of China, and the 2008 Financial Crisis, the study identifies trends that impact the development and spread of robotics technology. It also includes case studies of companies like Foxconn and Siemens, which shed light on the practical challenges and opportunities faced in different geopolitical and economic contexts. The findings emphasize the importance of geopolitical stability, regional dynamics, and workforce upskilling in the successful deployment of robotics. This research offers a comprehensive framework for businesses to navigate the complexities of international trade, geopolitical risks, and the changing robotics landscape, ultimately leading to improved operational efficiency and sustainable growth in a globalized market.

RETRACTED ARTICLEResearch Progress on 2D Human Pose Estimation Based on Deep Learning

Human pose estimation (HPE) is a significant area of study within computer vision and artificial intelligence, which locates the position and pose of human joints through images or videos. HPE has advanced progress in computer vision and deep learning fields at the theoretical level, improved the efficiency and accuracy of neural networks, and supported the development of natural and efficient human-computer interaction systems. At the application level, HPE has extensive value in many fields, including security monitoring, motion analysis and health management, VR&AR, robotics technology, film and television production and animation, intelligent driving and assisted driving. This paper divides 2D HPE tasks into three categories: two-stage (top-down and bottom-up), single-stage, and other improvement strategies (Transformer-based methods and post-processing optimization methods). Although deep learning-based pose estimation algorithms have achieved remarkable results, they still face challenges, such as prediction in complex scenes, crowd and joint occlusion problems, and lightweight design of models. Future work should pay more attention to these challenges and extend pose estimation technology from 2D to 3D contexts.

Exploring the viability of robotic technology integrated with Vivaldi artificial intelligence for functional assessment in amyotrophic lateral sclerosis

In this study, we explore the feasibility and efficacy of leveraging Sanbot Elf – a humanoid intelligent assistive robot – integrated with artificial intelligence (AI), specifically the Vivaldi AI system, for functional assessment in amyotrophic lateral sclerosis (ALS) patients. Our investigation involves evaluating and comparing the performance of the Sanbot Elf in administering the ALS Functional Rating Scale–Revised (ALSFRS-R) to that of human operators, using a structured format where patients respond with either “yes” or “no” answers. This approach is intentionally adopted to minimize ambiguity in patient responses. Patients were given the option to respond either verbally or by utilizing the touchscreen display, particularly beneficial for those experiencing dysarthria or hypophonia. In addition, we examined patient emotional responses to this novel approach. A cohort of 28 ALS patients participated in the study, with a subset undergoing longitudinal follow-up assessments. Our results demonstrate strong agreement between human and robotic administrations of the ALSFRS-R, indicating the potential for AI-enabled robotics to accurately assess ALS functional status. Furthermore, the patients’ feedback underscores their acceptability of this technology as a supportive tool in healthcare settings. Our findings also highlight the potential benefits of employing robotic devices with algorithmic capabilities, such as the binary tree method, in hospitals. Moreover, such integration has the potential to alleviate operators’ workload. Importantly, this research contributes to the burgeoning field of AI-enabled healthcare operations, highlighting the promising role of robotic systems in enhancing functional assessment and management of ALS.

Caribbean libraries 2.0: the robotic revolution in Caribbean academic library spaces

Purpose This paper is the genesis for robots and robotic technology and their introduction to the Caribbean Academic library community. This paper aims to explore the specific areas that this technology can improve as well as their adaptability and dynamic yet multifaceted nature it possesses. Design/methodology/approach A thorough assessment of literature was done of all developed libraries that are employing the services of robots and robotic technology in their daily operations. Additionally, a meticulous analysis was done of all Caribbean Libraries that have explored, are currently exploring or actively explored the implementation of robots and robotic technology for effective use in their libraries. Findings Seamless functionality as well as the reduction of mundane repetitive tasks by library staff is at the fore. Efficacy and heightened levels of accuracy are also found to be a great factor for implementation as well as speed of retrieval and offsite storage are further benefits to the implementation of robots and robotic technology. Research limitations/implications This research primarily assessed material on robotics and robotic technology that offers unprecedented efficacy and accuracy in the processing of information and tasks assigned as well as smooth location and retrieval of library material resulting in reduction in wait time for all library users. Originality/value To the best of the author’s knowledge, this paper is the first of its kind and is intended to trigger a “light bulb” in the minds of decision-makers and managers of Library spaces as to the potential robots and robotic technology has on fostering greater levels of efficacy in certain key areas of libraries and help improve user services while adding to the theoretical body of knowledge available in the field on this fast rising area.

Validity and reliability of the Chinese version of human–robot interaction self-efficacy scale in Chinese adults

BackgroundWith the fast-paced advancements of robot technology, human–robot interaction (HRI) has become increasingly popular and complex, and self-efficacy in HRI has received extensive attention. Despite its popularity, this topic remains understudied in China.ObjectiveIn order to provide a psychometrically sound instrument in China, this study aimed to translate and validate the Self-Efficacy in Human–Robot Interaction Scale (SE-HRI) in two Chinese adult samples (N1 = 300, N2 = 500).MethodsThe data was analyzed by SPSS 26.0 and Amos 24.0. Item analysis and exploratory factor analysis were conducted using Sample 1 data. Confirmatory factor analysis, criterion-related validity analysis, and reliability analysis were then performed using Sample 2 data.ResultsThe results revealed that the Chinese SE-HRI scale consisted of 13 items in a two-factor model, suggesting a good model fit. Moreover, general self-efficacy and willingness to accept the use of artificial intelligence (AI) were both positively correlated with self-efficacy in HRI, while negative attitudes toward robots showed an inverse correlation, proving the Chinese SE-HRI scale exhibited excellent criterion-related validity.ConclusionThe Chinese SE-HRI scale is a reliable assessment tool for evaluating self-efficacy in HRI in China. The study discussed implications and limitations, and suggested future directions.

Recent Advances in Robotic Surgery for Urologic Tumors.

This review discusses recent advances in robotic surgery for urologic tumors, focusing on three key areas: robotic systems, assistive technologies, and artificial intelligence. The Da Vinci SP system has enhanced the minimally invasive nature of robotic surgeries, while the Senhance system offers advantages such as tactile feedback and eye-tracking capabilities. Technologies like 3D reconstruction combined with augmented reality and fluorescence imaging aid surgeons in precisely identifying the anatomical relationships between tumors and surrounding structures, improving surgical efficiency and outcomes. Additionally, the development of artificial intelligence lays the groundwork for automated robotics. As these technologies continue to evolve, we are entering an era of minimally invasive, precise, and intelligent robotic surgery.

Robotic Technologies and Automation in Construction: A Systematic Review

The global construction industry is experiencing a high rate of disruption arising from the deployment of emerging robotic technologies and process automation. This study investigates research trends in robotic technologies and automation in the construction industry. Using topic-specific keywords to organise and summarise pertinent studies, the study undertook a systematic literature review and meta-analysis of robotic technologies and automation in construction. A systematic search of the databases of Scopus, Web of Science, and Dimensions was conducted, with a total of 9,515 journal articles retrieved from them. Based on inclusion and exclusion criteria, a total of 51 research papers met the parameters for meta analysis and systematic review. Data relating to the research papers' demography and to robotic technologies as well as automation in construction were mined, with a quantitative meta-analysis performed on them. The results show a spread of research efforts across Europe, Asia and America, with an increase in research output between 2019 and 2023. The results further show that construction gantry systems, bricklaying robots and 3D concrete printers are the most studied robotic technologies and automation processes in the sector. The study concludes that there is still a paucity of research on robotic technologies and automation in construction. The study therefore recommends further research on robotic technologies and automation in construction, especially with regard to their appropriate application and deployment in construction projects across Africa.

Spiritual Cyborg: Virtual Embodiment From Secular Ambiguities to Ontological Opportunities

Abstract AI and robotic technologies are reshaping embodied experience, specifically experiences of the relation of mind to body as well as experiences of “reality,” which necessitate the qualifiers augmented or virtual. Such technologies have allowed people to infuse the expanding assortment of technological experiences with spiritual meaning, thus expanding the ambit of spirituality and religiosity; at the same time, the technology has provided many researchers with occasion to argue that all spiritual and virtual experience—including of soul and deities—may only just ever be in the brain, putting the virtual back into the body but not without changing each. We are comparing three sites—VR, gaming, and transhuman mind uploading in Europe, the US, and Japan—not as sites of confusion but of “ontological opportunity,” that is, occasions for remaking experiences of embodiment and disembodiment, and changing the relation between reality and virtuality.

Breaking into the black box of customer perception towards robot service: Empirical evidence from service sector

The advent of artificial intelligence and machine learning has enabled robots to serve in consumer market for a better customer experience. Nevertheless, acceptance of robotic technology among consumers is still lacking. Therefore, this study has developed an integrated model with robot appearance, expectation confirmation model, diffusion of innovation and theory of planned behavior and empirically investigates customer intention to use service robot. The research model is empirically tested with 349 responses retrieved from customers visiting retail stores. Statistical results have revealed that customer innovativeness, compatibility, behavioral control, expectation confirmation, service robot appearance and subjective norms explained R2 80.1 % variance in customer attitude to use service robot. Practically, this research has suggested that policy makers should pay attention in innovativeness, compatibility, perceived behavioral control, expectation confirmation, robot appearance and subjective norms to boost robot service acceptance among customers. This study is original as it develops an integrated model with the combination robot appearance, theory of planned behavior, expectation confirmation and diffusion of innovation theory. In addition to that customer self-identity is conceptualized as moderating factor and hence distinguishing current research with past studies.

Optimasi Pengukuran Dinamis dari Visualisasi Model Ruangan 3D Menggunakan Sensor LiDAR dan Framework RoomPlan

Utilizing limited space to be more functional and aesthetic, such as adding furniture or using it as gardening space, can be achieved through effective room mapping. However, manual mapping methods have limitations such as inaccurate measurements, time efficiency, and also lack of room visualization. In this modern era, robotics technology has been widely applied in everyday life, one of which is the use of LiDAR sensors for room mapping. This paper discusses a room mapping system using a mobile application that utilizes LiDAR sensors. The mapping process is carried out by scanning the area to be mapped and rotating the area 360 degrees. The result of this mapping is a scanned 3D model of the room, which allows measurements from every side of the room. Research shows that the mapping results from the software created are similar in shape to actual field conditions. In addition, the measurement accuracy only has a small difference of 0.2%. It is hoped that this research can make it easier for humans to map rooms and make better use of limited space.

Deep Learning-Driven Robot Arm Control Fusing Convolutional Visual Perception and Predictive Modeling for Motion Planning

The wide application of robotic technology in various industries from industrial automation to medical assistance is gradually changing our production and lifestyle, and has attracted widespread attention in many fields. However, existing robotic control systems often grapple with limited flexibility and poor adaptability to complex environments, particularly in highly dynamic operational contexts. Against this backdrop, the integration of deep learning technologies offers new possibilities in enhancing robotic perception and decision-making, especially in visual perception and motion planning. To address these challenges, we have introduced a novel robotic arm control network model, MPC-WGAN-Faster R-CNN, which combines Model Predictive Control concepts with Wasserstein Generative Adversarial Networks and Faster R-CNN visual recognition technology. This integration aims to improve the precision and adaptability of robotic arm operations in complex environments.

A Comparative Study on the Application of Robotic Hair Restoration Technology Versus Traditional Follicular Unit Excision in Male Androgenetic Alopecia

ABSTRACTBackgroundThe robotic hair transplant technology, ARTAS, has a series of fine mechanical structure and an intelligent recognition system that allows it to independently select hair follicular units (FUs) and effectively harvest hair. After entering China in 2016, ARTAS has attracted the attention of hair transplant surgeons and hair loss patients given its advantages in a short learning curve and simple operation.ObjectiveTo compare the efficacy and safety between the ARTAS system and follicular unit excision (FUE) in the treatment of male androgenetic alopecia (AGA) and to further promote the improvement and upgrading of ARTAS technology concerning hair transplantation.MethodsThirteen Chinese male patients with Norwood–Hamilton II–IV AGA aged 25–35 years were enrolled in this study. The donor site of each patient was randomly divided into left and right regions, receiving ARTAS on one side and FUE on the other. Yield, transection, and discard rates of hair FUs from both sides were compared. Safety of the procedures in whole, as well as follow‐up results were investigated and evaluated.ResultsThe total yield rate on the ARTAS side was lower than on the FUE side (82.05% vs. 90.03%, p > 0.05); the total discard rate on the ARTAS side was higher than on the FUE side (10.71% vs. 5.46%, p < 0.05); the total transection rate on the ARTAS side was lower than on the FUE side (13.17% vs. 13.96%, p > 0.05). No significant difference was found in patient satisfaction (efficacy), and no side effects or complications were detected during or after all surgeries.ConclusionThe current iteration of Robotic hair transplant technology is effective and safe, and can be recommended for AGA hair transplantation surgery.

A new deepfake detection model for responding to perception attacks in embodied artificial intelligence

Embodied artificial intelligence (AI) represents a new generation of robotics technology combined with artificial intelligence, and it is at the forefront of current research. To reduce the impact of deepfake technology on embodied perception and enhance the security and reliability of embodied AI, this paper proposes a novel deepfake detection model with a new Balanced Contrastive Learning strategy, named BCL. By integrating unsupervised contrastive learning and supervised contrastive learning with deepfake detection, the model effectively extracts the underlying features of fake images from both individual level and category level, thereby leading to more discriminative features. In addition, a Multi-scale Attention Interaction module (MAI) is proposed to enrich the representative ability of features. By cross-fusing the semantic features of different receptive fields of the encoder, more effective deepfake traces can be mined. Finally, extensive experiments demonstrate that our method has good performance and generalization capabilities across intra-dataset, cross-dataset and cross-manipulation scenarios.

Increasing Trends of Artificial Intelligence With Robotic Process Automation in Health Care: A Narrative Review.

This review explores the fast-growing importance of artificial intelligence (AI) with robotic process automation (RPA) in healthcare. AI uses intelligent algorithms to analyze data, while RPA automates repetitive tasks to improve efficiency and accuracy. These technologies are swiftly revolutionizing health care by improving diagnostic precision, accelerating administrative tasks, reducing operation timing, and improving patient care. Application of these technologies requires good technical understanding, preparedness for continuous learning, and adaptability to new challenges. This review aims to provide an in-depth study of the potential applications, present implementations, challenges, and future scope of AI with RPA in healthcare. It can provide information to researchers, professionals, and decision-makers regarding the application of the technologies under consideration for better productivity, increased security and accuracy of data, cost reduction, and personalization of healthcare provided to patients. The main results are that AI and RPA can ensure greater data security, provide supporting work in administration, like scheduling appointments and medical billing, make better decisions, enable telehealth and remote patient monitoring, reduce human error, and increase overall health outcomes. This review overviews the challenges in implementing robotics technology, focusing mainly on secondary sourcejournals, scholarly articles, and reference books. Key findings indicate that this study reveals how robotics could alleviate healthcare professionals. Further research, investment, and collaboration will be needed to enable these technologies to reach their full potential for healthcare delivery. However, challenges such as data privacy and security concerns, high implementation costs, and regulatory and ethical considerations must be addressed. The conclusion emphasizes that while these technologies are revolutionizing healthcare by increasing efficiency and personalizing patient care, ongoing research, investment, and collaboration are essential for their successful adoption.

Intelligent machines as information and communication technology and their influence on sustainable marketing practices for beneficial impact on business performance: A conceptual framework

Intelligent machines are the machines or devices that make use of artificial intelligence and robotics technologies. It has the ability to accomplish a specific task in the presence of uncertainty and variability in its operating environment. Certainly, it can be used to support information and communication technology to streamline the creation, collection, processing, transmission, and storage of information for sustainable marketing practices. The flawless application of sustainable marketing practices results in beneficial impacts on business performance. In fact, the issue of unsustainable marketing practices can be effectively managed by intelligent machines. Therefore, this study is undertaken to uncover how intelligent machines can influence sustainable marketing practices for beneficial impacts on retailers’ business performance by proposing a unique conceptual framework. The theoretical contributions discuss two techno-sustainable marketing applications. First, intelligent machines improve incremental innovation. This allows retailers to balance technology risk with sustainable marketing and lower the cost of innovations. Second, intelligent machines increase business efficiency by automating sustainable marketing practices. This allows retailers to efficiently manage the inventory, improve fulfilment efficiency, and optimise stock levels. The managerial implications discuss two goals of sustainable marketing practices. First, it can attract sustainability-minded customers who support the retail business for their own well-being. Second, it builds a strong sustainable brand reputation that can lower the price sensitivity.

The rise of the machines: are robots the future of renal artery aneurysm repair? A systematic review.

Renal artery aneurysms (RAAs) are a rare vascular condition. Robot-assisted surgery offers a minimally invasive approach for RAA repair, potentially improving surgical outcomes. This review investigates the current evidence on the effectiveness and limitations of this technique. A systematic search following PRISMA guidelines identified relevant studies across five electronic databases. Studies investigating the use of robot-assisted surgery for RAA repair were included. The review identified 11 studies encompassing a total of 23 patients. Procedures included aneurysmectomy, end-to-end anastomosis, prosthetic graft repair, and even coil embolization. All surgeries were successful, with only minor complications reported in four cases. Robot-assisted RAA repair shows promise as a minimally invasive approach with encouraging preliminary outcomes. However, the limited data come from small studies. Future advancements in robotic technology hold the potential to optimize this approach for improved patient care.