A Stable Real-time AR Framework for Training and Planning in Industrial Environments

Extended-Reality Technologies: An Overview of Emerging Applications in Medical Education and Clinical Care.

Teaching, learning and training in assembly or disassembly as well as maintenance operation to new users, employees, engineers or technicians is important for various education sector and industries for them to acquire new skills. However to train those users to efficiently perform new skills is become challenging. It is important to reduce the user's training and working times to avoid cost issues in training, material, unavailable expertise and avoid actual part damage. Therefore, this study is conducted to design and develop a Virtual Reality (VR) and Augmented Reality (AR) system for learning and training platform. The valve assembly system was selected as a task for mechanical assembly system. This study was designed to find the influence of interactive learning method using AR system. The outcome from this study showed that learning and training in AR and VR system resulted in better to user skill performance. User learn and trained in a ARVR group gives positive feedback; very easy, practical and as a solution of the training process without using the actual one. While learning using interactive learning method such as AR resulted with better knowledge with less assembly error.

The major challenges of augmented reality (AR) systems and virtual reality (VR) systems are varifocal images for vergence-accommodation conflict (VAC) and vision corrections. In this paper, we design a liquid crystal (LC) lens set consisting of three LC lenses for varifocal images and vision corrections in AR and VR. Four operating modes of such a LC lens set present three electrically tunable lens powers: 0, -0.79 diopters, -2 diopters, and -3.06 diopters by means of manipulation of polarization of incident light using electrically tunable half-wave-plates. The response time is fast(< 50 ms). We also demonstrate AR and VR systems by adopting the LC lens set to exhibit functions of varifocal images and vision corrections which enable to solve VAC as well as vision problem in AR and VR.

Virtual reality (VR) and augmented reality (AR) systems are increasingly available to neurosurgeons. These systems may provide opportunities for technical rehearsal and assessments of surgeon performance. The assessment of neurosurgeon skill in VR and AR environments and the validity of VR and AR feedback has not been systematically reviewed. A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted through MEDLINE and PubMed. Studies published in English between January 1990 and February 2021 describing the use of VR or AR to quantify surgical technical performance of neurosurgeons without the use of human raters were included. The types and categories of automated performance metrics (APMs) from each of these studies were recorded. Thirty-three VR studies were included in the review; no AR studies met inclusion criteria. VR APMs were categorized as either distance to target, force, kinematics, time, blood loss, or volume of resection. Distance and time were the most well-studied APM domains, although all domains were effective at differentiating surgeon experience levels. Distance was successfully used to track improvements with practice. Examining volume of resection demonstrated that attending surgeons removed less simulated tumor but preserved more normal tissue than trainees. More recently, APMs have been used in machine learning algorithms to predict level of training with a high degree of accuracy. Key limitations to enhanced-reality systems include limited AR usage for automated surgical assessment and lack of external and longitudinal validation of VR systems. VR has been used to assess surgeon performance across a wide spectrum of domains. The VR environment can be used to quantify surgeon performance, assess surgeon proficiency, and track training progression. AR systems have not yet been used to provide metrics for surgeon performance assessment despite potential for intraoperative integration. VR-based APMs may be especially useful for metrics that are difficult to assess intraoperatively, including blood loss and extent of resection.

Introduction: Augmented Reality (AR) systems are systems in which users view and interact with virtual objects overlaying the real world. AR systems are used across a variety of disciplines, i.e., games, medicine, and education to name a few. Optical See-Through (OST) AR displays allow users to perceive the real world directly by combining computer-generated imagery overlaying the real world. While perception of depth and visibility of objects is a widely studied field, we wanted to observe how color, luminance, and movement of an object interacted with each other as well as external luminance in OST AR devices. Little research has been done regarding the issues around the effect of virtual objects’ parameters on depth perception, external lighting, and the effect of an object’s mobility on this depth perception.Methods: We aim to perform an analysis of the effects of motion cues, color, and luminance on depth estimation of AR objects overlaying the real world with OST displays. We perform two experiments, differing in environmental lighting conditions (287 lux and 156 lux), and analyze the effects and differences on depth and speed perceptions.Results: We have found that while stationary objects follow previous research with regards to depth perception, motion and both object and environmental luminance play a factor in this perception.Discussion: These results will be significantly useful for developers to account for depth estimation issues that may arise in AR environments. Awareness of the different effects of speed and environmental illuminance on depth perception can be utilized when performing AR or MR applications where precision matters.

Augmented reality (AR) is a new human-computer interaction technology that combines virtual reality, computer vision, and computer networks. With the rapid advancement of the medical field towards intelligence and data visualisation, AR systems are becoming increasingly popular in the medical field because they can provide doctors with clear enough medical images and accurate image navigation in practical applications. However, it has been discovered that different display types of AR systems have different effects on doctors' perception of the image after virtual-real fusion during the actual medical application. If doctors cannot correctly perceive the image, they may be unable to correctly match the virtual information with the real world, which will have a significant impact on their ability to recognise complex structures. This paper uses Citespace, a literature analysis tool, to visualise and analyse the research hotspots when AR systems are used in the medical field. A visual analysis of the 1163 articles retrieved from the Web of Science Core Collection database reveals that display technology and visualisation technology are the key research directions of AR systems at the moment. This paper categorises AR systems based on their display principles, reviews current image perception optimisation schemes for various types of systems, and analyses and compares different display types of AR systems based on their practical applications in the field of smart medical care so that doctors can select the appropriate display types based on different application scenarios. Finally, the future development direction of AR display technology is anticipated in order for AR technology to be more effectively applied in the field of smart medical care. The advancement of display technology for AR systems is critical for their use in the medical field, and the advantages and disadvantages of various display types should be considered in different application scenarios to select the best AR system.

This paper describes the collaborative augmented reality (AR) system with which multiple users can handwrite 3D lines in the air simultaneously and manipulate the lines directly in the real world. In addition, we propose a new technique for embodied communication utilizing the 3D drawing exercise. Up to now, the various 3D user interfaces have been proposed. Although most of them aim to solve the specific problems in the virtual environments, the possibility of the 3D drawing expression has not been explored yet. Accordingly, we paid special attention to the interaction with the real objects in daily life, and considered to manipulate real objects and 3D lines without any distinctions by the same action. The developed AR system consists of a head-mounted display, a drawing tool, 6DOF sensors, and the 3D user interface, which enables to push, grasp and pitch a 3D lines directly by use of the drawing tool. Additionally users can pick up desired color from either a landscape or a virtual line through the direct interaction with this tool. For sharing 3D lines among multiple users at the same place, the distributed-type AR system has been developed that mutually sends and receives drawn data between systems. With the developed system, users can proceed to design jointly in the real space through arranging each 3D drawing by direct manipulation. Moreover, a new application to the entertainment has become possible to play sports like catch, fencing match, or the like

In recent years, hardware and software advances in digital technology have prompted not only the commercial use of augmented reality (AR) systems, but its implementation in education. Marker-based AR systems allow users to input pre-designed markers, and generate new scenes blending together the real world and computer-generated 3D images. Nevertheless, few AR systems permit simultaneous interactions of multiple markers. This study aims to construct an interactive multimedia learning system. The story script showcases the growth of flowers by applying a series of markers, where interactions with 3D objects can be achieved through AR technology. Learners can use a camera to capture the information of multiple AR markers, and 3D objects and media can be generated on-screen. With variations in AR markers, and time changes of the Arduino Clock, one can learn the growth of plants during day and night through a mixed-reality virtual experience that brings fun to learning. Accordingly, this e-learning system is capable of boosting students' learning interests and improving their learning effectiveness.

Abstract. The attempt to work out the geomatic workflow of transforming low-level aerial imagery obtained with unmanned aerial vehicles (UAV) into a digital terrain model (DTM) and implementing the 3D model into the augmented reality (AR) system constitutes the main problem discussed in this article. The authors suggest the following workflow demonstrated in Fig. 1.The series of pictures obtained by means of UAV equipped with a HD camera was the source of data to be worked out in the final stage of the geovisualization. The series was then processed and a few point clouds were isolated from it, being later used for generating test 3D models.The practical aim of the research conducted was to work out, on the basis of the UAV pictures, the 3D geovisualization in the AR system that would depict the heap of the natural aggregate of irregular shape. The subsequent aim was to verify the accuracy of the produced 3D model. The object of the study was a natural aggregate heap of irregular shape and denivelations up to 11 meters.Based on the obtained photos, three point clouds (varying in the level of detail) were generated for the 20 000-meter-square area. The several-centimeter differences observed between the control points in the field and the ones from the model might corroborate the usefulness of the described algorithm for creating large-scale DTMs for engineering purposes. The method of transformation of pictures into the point cloud that was subsequently transformed into 3D models was employed in the research, resulting in the scheme depicting the technological sequence of the creation of 3D geovisualization worked out in the AR system. The geovisualization can be viewed thanks to a specially worked out mobile application for smartphones.

Augmented Reality Systems (ARS) attempt to enhance humans’ perception of their indoors and outdoors working and living environments and understanding of tasks that they need to carry out. The enhancement is effected by complementing the human senses with virtual input. For example, when the human visual sense is enhanced, an ARS allows virtual objects to be superimposed on a real world by projecting the virtual objects onto real objects. This provides the human user of the ARS with additional information that he/she could not perceive with his/her senses. In order to receive the virtual input and sense the world around them augmented with real time computer-generated features, users of an ARS need to wear special equipment, such as head-mounted devices or wearable computing gears. Tracking technologies are very important in an ARS and, in fact, constitute one challenging research and development topic. Tracking technologies involve both hardware and software issues, but in this chapter we focus on tracking computation. Tracking computation refers to the problem of estimating the position and orientation of the ARS user’s viewpoint, assuming the user to carry a wearable camera. Tracking computation is crucial in order to display the composed images properly and maintain correct registration of real and virtual worlds. This tracking problem has recently become a highly active area of research in ARS. Indeed, in recent years, several approaches to vision-based tracking using a wearable camera have been proposed, that can be classified into two main categories, namely “marker-based tracking” and “marker-less tracking.” In this chapter, we provide a concise introduction to vision-based tracking for mobile ARS and present an overview of the most popular approaches recently developed in this research area. We also present several practical examples illustrating how to conceive and to evaluate such systems.

Endoscopic surgery causes less tissue injury compared to open surgical techniques, thus promoting more rapid recuperation and reduced post-operative pain. Endoscopy, however, allows the surgeon to visualise only the anatomical surface of the surgical site, with a relatively narrow field of view. Moreover, the 2D video captured by the conventional endoscope does not provide depth perception of the surgical scene. In this study, these limitations have been addressed with the development of an augmented reality (AR) system with stereoscopic visualisation. A phantom and its 3D CT model were used, respectively, to form the real and virtual parts of the AR. The virtual environment camera pose was tracked using algorithms for image feature detection, feature matching and Perspective-n-Point applied on the endoscopic image and the 3D virtual model-rendered image. The endoscope video frame- and the virtual model-rendered images were superimposed to form the AR composite view. The depth buffer (z-buffer) of the rendering window was further used to make a stereo pair of the AR image. The AR system produced a stereo composite view having well-aligned real and virtual components. The RMS error of the real and virtual image contours registration was 9.6 ± 6.7 mm. Correlation coefficients between the depth map from z-buffer and a depth camera was between 0.60 and 0.96 (p < 0.05). The AR system requires further improvement to be applicable at a higher frame rate of endoscope image acquisition. It also needs to include motion and deformation models when applied to animals or patients.

With computer vision-based technologies, current Augmented reality (AR) systems can effectively recognize multiple objects with different visual characteristics. However, only limited degrees of distinctions can be offered among different objects with similar natural features, and inherent information about these objects cannot be effectively extracted. In this paper, we propose TaggedAR, i.e., an RFID-based approach to assist the recognition of multiple tagged objects in AR systems, by deploying additional RFID antennas to the COTS depth camera. By sufficiently exploring the correlations between the depth of field and the received RF-signal, we propose a rotate scanning-based scheme to distinguish multiple tagged objects in the stationary situation, and propose a continuous scanning-based scheme to distinguish multiple tagged human subjects in the mobile situation. By pairing the tags with the objects according to the correlations between the depth of field and RF-signals, we can accurately identify and distinguish multiple tagged objects to realize the vision of “tell me what I see” from the AR system. We have implemented a prototype system to evaluate the actual performance with case studies in a real-world environment. The experiment results show that our solution achieves an average match ratio of 91 percent in distinguishing up to dozens of tagged objects with a high deployment density.

A flat lens with a tunable focal length that does not require mechanical movement is highly desirable in augmented reality (AR) or virtual reality (VR) systems, but its development poses significant challenges. A colloidal lens that uses dielectrophoretic (DEP) manipulation of nanoparticle density in a colloid can be a good solution for achieving tunability in flat lenses. In this study, we investigated the optical properties of a nanocolloidal lens containing two-dimensional (2D) α-zirconium phosphate (α-ZrP) nanoparticles and optimized the lens design parameters to achieve low image distortion and large focal length tunability. We simulated the nanoparticle distribution function as a function of applied voltage for various lenses with different electrode designs, and the simulation results matched well with experimental observations. Additionally, we identified a condition for lower power consumption. Finally, we identified specific design parameters that allow for wide focal length control without image deformation and utilized them to fabricate lenses for a simple AR system. This study clearly demonstrates the potential of tunable nanocolloidal lenses, particularly in AR systems, by optimizing their design and performance.

Integrating Augmented Reality in the Assembly Domain - Fundamentals, Benefits and Applications

Recent technological innovations have created new opportunities for the increased adoption of virtual reality (VR) and augmented reality (AR) applications in medicine. While medical applications of VR have historically seen greater adoption from patient-as-user applications, the new era of VR/AR technology has created the conditions for wider adoption of clinician-as-user applications. Historically, adoption to clinical use has been limited in part by the ability of the technology to achieve a sufficient quality of experience. This article reviews the definitions of virtual and augmented reality and briefly covers the history of their development. Currently available options for consumer-level virtual and augmented reality systems are presented, along with a discussion of technical considerations for their adoption in the clinical environment. Finally, a brief review of the literature of medical VR/AR applications is presented prior to introducing a comprehensive conceptual framework for the viewing and manipulation of medical images in virtual and augmented reality. Using this framework, we outline considerations for placing these methods directly into a radiology-based workflow and show how it can be applied to a variety of clinical scenarios.