Intuitive Operation Research Articles

MultiShape: a spectral element method, with applications to Dynamic Density Functional Theory and PDE-constrained optimization

Abstract A new numerical framework is developed to solve general nonlinear and nonlocal PDEs on complicated two-dimensional domains. This enables the solution of a wide range of both steady and time-dependent problems on nonstandard geometries, as well as providing the ability to impose nonlinear and nonlocal boundary conditions (typical of those arising in the modelling of physical phenomena) in a flexible and automated way. This spectral element methodology, which we called MultiShape, is compatible with other state-of-the-art numerical methods, such as differential–algebraic equation solvers and optimization algorithms. MultiShape is an open-source Matlab library, in which the numerical implementation is designed to be user-friendly: the problem set-up and computations are done automatically through intuitive operator definitions and notation. Validation tests are presented, before we showcase the power and versatility of MultiShape with three motivating examples in Dynamic Density Functional Theory and PDE-constrained optimization.

An intuitive guidewire control mechanism for robotic intervention.

Teleoperated Interventional Robotic systems (TIRs) are developed to reduce radiation exposure and physical stress of the physicians and enhance device manipulation accuracy and stability. Nevertheless, TIRs are not widely adopted, partly due to the lack of intuitive control interfaces. Current TIR interfaces like joysticks, keyboards, and touchscreens differ significantly from traditional manual techniques, resulting in a shallow, longer learning curve. To this end, this research introduces a novel control mechanism for intuitive operation and seamless adoption of TIRs. An off-the-shelf medical torque device augmented with a micro-electromagnetic tracker was proposed as the control interface to preserve the tactile sensation and muscle memory integral to interventionalists' proficiency. The control inputs to drive the TIR were extracted via real-time motion mapping of the interface. To verify the efficacy of the proposed control mechanism to accurately operate the TIR, evaluation experiments using industrial grade encoders were conducted. A mean tracking error of 0.32 ± 0.12mm in linear and 0.54 ± 0.07° in angular direction were achieved. The time lag in tracking was found to be 125ms on average using pade approximation. Ergonomically, the developed control interface is 3.5mm diametrically larger, and 4.5g. heavier compared to traditional torque devices. With uncanny resemblance to traditional torque devices while maintaining results comparable to state-of-the-art commercially available TIRs, this research successfully provides an intuitive control interface for potential wider clinical adoption of robot-assisted interventions.

A virtual reality-based immersive teleoperation system for remote human-robot collaborative manufacturing

In recent years, the cutting-edge technologies in smart manufacturing have presented promising opportunities for the utilization of human-robot collaborative teleoperation in personalized manufacturing tasks. To effectively leverage the creative capabilities of humans while benefiting from the efficiency and stability of robots, the provision of an intuitive teleoperation interface assumes paramount importance. However, current teleoperation systems still face limitations in terms of intuitive operability. In this study, we present a virtual reality-based teleoperation system that offers operators a more intuitive interaction platform for robot control, thereby facilitating personalized manufacturing processes. The overall system framework design, as well as the main components are elaborated in detail. Furthermore, an evaluative case study based on the battery disassembly task is conducted to assess the performance of the proposed system. The results demonstrate that the proposed teleoperation system exhibits improved intuitiveness.

Enhancing educational experience through establishing a VR database in craniosynostosis: report from a single institute and systematic literature review.

Craniosynostosis is a type of skull deformity caused by premature ossification of cranial sutures in children. Given its variability and anatomical complexity, three-dimensional visualization is crucial for effective teaching and understanding. We developed a VR database with 3D models to depict these deformities and evaluated its impact on teaching efficiency, motivation, and memorability. We included all craniosynostosis cases with preoperative CT imaging treated at our institution from 2012 to 2022. Preoperative CT scans were imported into SpectoVR using a transfer function to visualize bony structures. Measurements, sub-segmentation, and anatomical teaching were performed in a fully immersive 3D VR experience using a headset. Teaching sessions were conducted in group settings where students and medical personnel explored and discussed the 3D models together, guided by a host. Participants' experiences were evaluated with a questionnaire assessing understanding, memorization, and motivation on a scale from 1 (poor) to 5 (outstanding). The questionnaire showed high satisfaction scores (mean 4.49 ± 0.25). Participants (n = 17) found the VR models comprehensible and navigable (mean 4.47 ± 0.62), with intuitive operation (mean 4.35 ± 0.79). Understanding pathology (mean 4.29 ± 0.77) and surgical procedures (mean 4.63 ± 0.5) was very satisfactory. The models improved anatomical visualization (mean 4.71 ± 0.47) and teaching effectiveness (mean 4.76 ± 0.56), with participants reporting enhanced comprehension and memorization, leading to an efficient learning process. Establishing a 3D VR database for teaching craniosynostosis shows advantages in understanding and memorization and increases motivation for the study process, thereby allowing for more efficient learning. Future applications in patient consent and teaching in other medical areas should be explored.

Use and Design of Virtual Reality-Supported Learning Scenarios in the Vocational Qualification of Nursing Professionals: Scoping Review.

Numerous reviews advocate using virtual reality (VR) in educational contexts. This medium allows learners to test experiences in realistic environments. Virtually supported scenarios offer a safe and motivating way to explore, practice, and consolidate nursing skills in rare and critical nursing tasks. This is also cited as one of the reasons why VR can significantly increase the knowledge acquisition of nursing students. Nevertheless, studies are limited in their significance owing to the chosen design. Despite great interest, this results in a low level of confidence in VR as a curricular teaching method for nursing education. Therefore, defining concrete design and didactic-methodological parameters that support teachers in the use and implementation of VR is more relevant. This scoping review aims to provide an overview of significant design aspects for VR scenario conception and its transfer to generalist nursing education to generate value for the development of teaching scenarios and their sustainable implementation in teaching. A comprehensive literature search was performed using the MEDLINE (via PubMed) and CINAHL databases, and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist was applied. The search was conducted from May to July 2022, using a specific search principle corresponding to the focus and the growing study corpus. A previously defined "population, concept, and context" scheme was employed as the basis for the double-blind review of all relevant international German and English publications released up to May 1, 2022. In accordance with the predefined selection procedure, 22 publications were identified. The identified aspects aided in the development of design, didactic, and research recommendations. The intuitive operation of realistically designed VR scenarios, which are standardized, reliable, and modifiable, as well as clear instructions and specific multimodal feedback functions were described positively. The same applied to the linear structure of the sequences with graduated demands and high image quality for increased immersion with low sensory overload. Changes in perspectives, multiuser options, dialogs, and recording functions can contribute to an interactive care practice. On the research side, it is advisable to define VR terminologies. In addition to considering larger samples, varying settings, and financial issues, it is recommended to conduct long-term studies on knowledge acquisition or improved patient outcomes. VR scenarios offer high potential in the context of nursing education if teachers and learners develop them co-creatively according to design features and implement them by means of a well-conceived concept. VR enables trainees to develop practical skills continuously in a standardized way. In addition, its deployment supports the sensitization of trainees to digital nursing technologies and the expansion of their digital skills in a practical setting. Furthermore, it allows sustainability issues to be addressed.

JVC-02 Teleoperated Robot: Design, Implementation, and Validation for Assistance in Real Explosive Ordnance Disposal Missions

Explosive ordnance disposal (EOD) operations are hazardous due to the volatile and sensitive nature of these devices. EOD robots have improved these tasks, but their high cost limits accessibility for security institutions that do not have sufficient funds. This article presents the design, implementation, and validation of a low-cost EOD robot named JVC-02, specifically designed for use in explosive hazardous environments to safeguard the safety of police officers of the Explosives Disposal Unit (UDEX) of Arequipa, Peru. To achieve this goal, the essential requirements for this type of robot were compiled, referencing the capabilities of Rescue Robots from RoboCup. Additionally, the Quality Function Deployment (QFD) methodology was used to identify the needs and requirements of UDEX police officers. Based on this information, a modular approach to robot design was developed, utilizing commercial off-the-shelf components to facilitate maintenance and repair. The JVC-02 was integrated with a 5-DoF manipulator and a two-finger mechanical gripper to perform dexterity tasks, along with a tracked locomotion mechanism, which enables effective movement, and a three-camera vision system to facilitate exploration tasks. Finally, field tests were conducted in real scenarios to evaluate and experimentally validate the capabilities of the JVC-02 robot, assessing its mobility, dexterity, and exploration skills. Additionally, real EOD missions were carried out in which UDEX agents intervened and controlled the robot. The results demonstrate that the JVC-02 robot possesses strong capabilities for real EOD applications, excelling in intuitive operation, low cost, and ease of maintenance.

Usability Testing of Novel IoT-Infused Digital Services on Farm Equipment Reveals Farmer’s Requirements towards Future Human–Machine Interface Design Guidelines

The application of digital technologies in the agricultural sector is increasing. One of the new key technologies is the Internet of Things (IoT), which can facilitate the everyday work of farmers. For the successful adoption of IoT-enabled digital products and to ensure improved workflows, the usability of human–machine interfaces is highly important. Various design approaches of human–machine interfaces (HMIs) can currently be found in the monitoring of agricultural machinery. In this work, the most well-known HMIs are considered. Based on a usability test (participants n = 9), the user interface (UI) of a novel mobile application (NEVONEX Cockpit App) was chosen as an example of a design approach of an IoT ecosystem that is oriented towards the UI design of mobile applications. This work aims to identify the weak points of this UI. Conclusions about the needs, and thus an improvement of the user experience, are based on the suggestions for improvement and the information about the general requirements of farmers for a UI for agricultural machinery. Here, it was found that most farmers are satisfied with the UI design of their familiar tractor monitors. According to the survey, the three most important points to be considered in the UI design are intuitive operation and menu navigation, easy access to the essential functions and buttons, and sufficiently large control panels. The conducted usability tests can be considered a basis for developing HMIs for agriculture machinery. Through repeated execution of comparable usability tests, there is the possibility of developing future HMI guidelines for agriculture to improve the user experience (UX). For the NEVONEX ecosystem, feedback from the user interface testing was incorporated in a major revision of the Cockpit App’s design, where a lot more display space was given to the agronomic digital services by smartly arranging infrastructure functions in tiles.

TorchQL: A Programming Framework for Integrity Constraints in Machine Learning

Finding errors in machine learning applications requires a thorough exploration of their behavior over data. Existing approaches used by practitioners are often ad-hoc and lack the abstractions needed to scale this process. We present TorchQL, a programming framework to evaluate and improve the correctness of machine learning applications. TorchQL allows users to write queries to specify and check integrity constraints over machine learning models and datasets. It seamlessly integrates relational algebra with functional programming to allow for highly expressive queries using only eight intuitive operators. We evaluate TorchQL on diverse use-cases including finding critical temporal inconsistencies in objects detected across video frames in autonomous driving, finding data imputation errors in time-series medical records, finding data labeling errors in real-world images, and evaluating biases and constraining outputs of language models. Our experiments show that TorchQL enables up to 13x faster query executions than baselines like Pandas and MongoDB, and up to 40% shorter queries than native Python. We also conduct a user study and find that TorchQL is natural enough for developers familiar with Python to specify complex integrity constraints.

In the beginning, there was the analogue. An alternative history of the beginnings of computer art

Since the late 1960s, the historiography of computer art has been developing a canon that is progressively broadening. However, this canon reveals significant blind spots, particularly due to the predominant success of digital computers leading to computer art being almost exclusively identified with digital technology. This identification overlooks other significant classes of computers, notably analogue and hybrid systems, leaving the contributions, artworks, and ideas of many early pioneers in the field unrecognized. Consequently, the history of art created with analogue and hybrid computers remains largely unexplored both in art history and media archaeology. This article seeks to illuminate this relatively obscure chapter of history by introducing the individuals and projects that utilized analogue computers, drawing on previously unknown historical sources. The aim is to underscore the historical significance of a technology that is currently experiencing a resurgence of interest in the field of computer science. The findings reveal that before the advent of artistic experiments with digital computers, analogue computers were the subject of pioneering exploration. The real-time intuitive operation of analogue computers was a unique advantage, foreshadowing a human-machine relationship now commonplace with digital technology. The narrative of the analogue computer constitutes an essential domain for understanding the diversity of computing technologies at the dawn of the computer age. Despite the scarcity of sources documenting these artistic endeavors, this article serves as a call to action for further research in this neglected area.

A penicillinase-modified poly(N-isopropylacrylamide-co-acrylamide) smart hydrogel biosensor with superior recyclability for sensitive and colorimetric detection of penicillin G

Antibiotics are widely used for treating bacterial infections. However, excessive or improper use of antibiotics can pose a serious threat to human health and water environments, and thus, developing cost-effective, portable and effective strategies to analyze and detect antibiotics is highly desired. Herein, we reported a responsive photonic hydrogel (RPH)-based optical biosensor (PPNAH) with superior recyclability for sensitive and colorimetric determination of a typical β-lactam antibiotic penicillin G (PG) in water. This sensor was composed of poly(N-isopropylacrylamide-co-acrylamide) smart hydrogel with incorporated penicillinase and Fe3O4@SiO2 colloidal photonic crystals (CPCs). The sensor could translate PG concentration signals into changes in the diffraction wavelength and structural color of the hydrogel. It possessed high sensitivity and selectivity to PG and excellent detection performances for other two typical β-lactam antibiotics. Most importantly, due to the unique thermosensitivity of the poly(N-isopropylacrylamide) moieties in the hydrogel, the PG-responded PPNAH sensor could be facilely regenerated via a simple physical method at least fifty times while without compromising its response performance. Besides, our sensor was suitable for monitoring the PG-contaminated environmental water and displayed satisfactory detection performances. Such a sensor possessed obvious advantages of superior recyclability, highly chemical stability, low production cost, easy fabrication, wide range of visual detection, simple and intuitive operation for PG detection, and environmental-friendliness, which holds great potential in sensitive and colorimetric detection of the PG residues in polluted water.

New Injection Controls Environment for the Taiwan Light Source

Taiwan Light Source (TLS) has been service for user service since 1993. Several legacy systems have recently been updated in order to remove obsolescent parts and provide higher operating efficiency. Proprietary designed timing modules were recently replaced by an event based timing system. The magnets of the booster synchrotron were configured as three White circuits and driven by resonance excitation. The original control of the White circuits, which included an analogue amplitude loop and digital phase loop for regulation, has been replaced by full digital regulation loops. The successful upgrade of both systems has led to easy and smooth injection control with enhanced functionality and flexibility. The injection control includes foreground and background processes that coordinate the operation of e-gun, linear accelerator, booster synchrotron, and storage ring with the help of timing system. The injection control GUI provides an intuitive operation interface that includes parameter setting and all necessary information displays, such as various timing value, stored beam current/lifetime, injection efficiency, filling pattern, kickers waveform and so on. Energy saving mode of White circuits operation are supported and embedded into injection control to save electricity. Lifetime calculation of the storage ring is also synchronized with the injection process. Implementation details and operation experience will be presented.

Enhancing Human-Robot Collaboration in Industry 4.0 with AI-driven HRI

Human-robot interaction (HRI) is an important consideration in mechatronic design to ensure safe and intuitive operation of robotic systems. With advancements in artificial intelligence (AI), new opportunities have emerged to enhance HRI through learned models that can adapt to human behavior and preferences. This paper provides a comprehensive review of techniques to integrate AI into HRI for mechatronic systems. An overview is first provided of challenges and objectives in integrating intelligence into robotics for effective HRI. Modern approaches utilizing neural networks, reinforcement learning, and graph neural networks are then discussed for robotic perception, decision-making, motion control, and interaction adaptation. Additionally, hybrid approaches combining rule-based methods with learned models are highlighted. Guidelines are provided for collecting human interaction data, evaluating integrated system performance, and considering adjustability, explainability, and safety. Multiple tables summarize key studies on AI-enhanced user interfaces, interactive task learning, socially aware navigation, bio-inspired sensorimotor control, and personalized robots. Finally, open issues and future outlook are discussed. This paper aims to support mechatronic designers through an structured analysis of the emerging field of intelligent HRI with insights into current best practices for integration.

Voice user interfaces in manufacturing logistics: a literature review

AbstractDue to the increasing digitalization in manufacturing logistics, devices to integrate the worker into the digital manufacturing system are necessary. A voice user interface (VUI) can be considered suitable for this purpose due to its flexibility and intuitive operability. Despite the popularity and acceptance of VUIs in everyday life, their use in industrial applications, especially in manufacturing logistics, is still rare. While VUIs have been successfully used in order picking for decades, hardly any other industrial fields of application exist. In this paper, we have identified various barriers to the use of VUI in industrial applications. We categorized them and identified four key barriers. We then conducted a systematic literature review to determine and compare already investigated application areas of VUIs, their characteristics, advantages and disadvantages. We found that in particular the operation of machines and industrial robots, as well as general data and information output on machine and system status, maintenance and employee training are frequently investigated. It is noticeable that VUIs are often used in combination with other user interfaces (UIs). Some challenges to VUI usage, such as high ambient noise levels, have already been solved through various approaches, while other challenges remain. Based on the results of the literature review, we put forward a research agenda regarding further suitable industrial application areas as well as general challenges for the use of VUIs in industrial environments.

SEMG-based prediction of human forearm movements utilizing a biomechanical model based on individual anatomical/ physiological measures and a reduced set of optimization parameters.

For assistive devices such as active orthoses, exoskeletons or other close-to-body robotic-systems, the immediate prediction of biological limb movements based on biosignals in the respective control system can be used to enable intuitive operation also by untrained users e.g. in healthcare, rehabilitation or industrial scenarios. Surface electromyography (sEMG) signals from the muscles that drive the limbs can be measured before the actual movement occurs and, hence, can be used as source for predicting limb movements. The aim of this work was to create a model that can be adapted to a new user or movement scenario with little measurement and computing effort. Therefore, a biomechanical model is presented that predicts limb movements of the human forearm based on easy to measure sEMG signals of the main muscles involved in forearm actuation (lateral and long head of triceps and short and long head of biceps). The model has 42 internal parameters of which 37 were attributed to 8 individually measured physiological measures (location of acromion at the shoulder, medial/lateral epicondyles as well as olecranon at the elbow, and styloid processes of radius/ulna at the wrist; maximum muscle forces of biceps and triceps). The remaining 5 parameters are adapted to specific movement conditions in an optimization process. The model was tested in an experimental study with 31 subjects in which the prediction quality of the model was assessed. The quality of the movement prediction was evaluated by using the normalized mean absolute error (nMAE) for two arm postures (lower, upper), two load conditions (2 kg, 4 kg) and two movement velocities (slow, fast). For the resulting 8 experimental combinations the nMAE varied between nMAE = 0.16 and nMAE = 0.21 (lower numbers better). An additional quality score (QS) was introduced that allows direct comparison between different movements. This score ranged from QS = 0.25 to QS = 0.40 (higher numbers better) for the experimental combinations. The above formulated aim was achieved with good prediction quality by using only 8 individual measurements (easy to collect body dimensions) and the subsequent optimization of only 5 parameters. At the same time, just easily accessible sEMG measurement locations are used to enable simple integration, e.g. in exoskeletons. This biomechanical model does not compete with models that measure all sEMG signals of the muscle heads involved in order to achieve the highest possible prediction quality.

Development of Haptic Prosthetic Hand for Realization of Intuitive Operation for Physically Challenged

Development of Haptic Prosthetic Hand for Realization of Intuitive Operation for Physically Challenged

Design and Implementation of Haptic Prosthetic Hand for Realization of Intuitive Operation

Abstract: This project presents the design and implementation of a microcontroller-based voice activated wireless automation and hand movement system replicating using flex sensor system. As speech is the preferred mode of communication for human beings, this project intends to make the voice-oriented command for controlling the hand movements. The voice command is user independent. The system comprises of transmitting section and receiving section. Initially, the voice command is stored in the data base with the help of the function keys. Later the input voice commands are transmitted to through wireless device. The voice received is processed in the voice recognition system where the feature of the voice command is extracted and matched with the existing sample in the database. The module recognizes the voice and sends control messages to the microcontroller. This project also focuses on replicating the movements of the human hand using a plastic 3D printed hand simulation (hand frame). The flex sensors and servo motors work in co-ordination with ARDUINO to achieve this. The sensor sends the value to the ARDUINO, the ARDUINO processes the data and sends it to the servo motors. Based on the values provided the motor moves and thus the movement of the prosthetic hand is observed-replicating the motion of the hand.The functionality of the proposed project is based on myo-electric arm

High-precision measurement and control technology combined with intuitive operation

The general conditions for battery production and printed electronics are challenging: strict industry specifications for quality and price on the one hand, and scarcity of resources and an increasing shortage of skilled workers on the other. Against this background, efficient processes are crucial for economic success. In OPE journal, Florian Kortekamp, Project & Business Development Manager at BST GmbH, talks about technical innovations that specifically defuse this situation.

Perceived Website Efficacy for Life Insurance Companies

Given the proliferation of websites which act as digital channels for life insurance companies, a competitive situation has emerged with each vying for the web user's attention and patronage. Web efficacy is vital for creating an impressive online experience and gaining customer patronage. To facilitate the understanding of website managers on specific aspects which matter the most to customers, this study employs the best-worst method to evaluate the importance of various criteria employed by the web users to assess these digital options. Additionally, using four life insurance websites (LIC, SBI Life, HDFC Life Insurance, and Max Life Insurance) as alternatives, the study helps illustrate the competitive position of the websites based on key criteria: trust, visual appeal, innovativeness, information fit-to-task, tailored information, response time, intuitive operations, and relative advantage. The results of this study are easily interpretable and can provide key insights on the specific attributes in a comparative manner for website administrators and managers.

Visualized Stacked Denoising Auto-Encoder Model for Extracting and Evaluating the State Features of Rolling Bearings

Extracting intuitive operating state features from vibration signals without prior knowledge is a prospective requirement for health monitoring and fault diagnosis in bearings. In this paper, a visualized stacked denoising auto-encoder (VSDAE) model is proposed for the unsupervised extraction and quantitative evaluation of bearings’ state features. First, the stacked denoising auto-encoder (SDAE) was used to reconstruct vibration signals. The intermediate vector of the SDAE, which is a high-information-density representation of vibration signals, was regarded as the pending state feature. Then, the dimension of the intermediate vector was reduced by the t-distributed stochastic neighbor embedding (t-SNE) method to the two-dimensional visualization space. Finally, the silhouette coefficient of feature distribution was calculated to quantitatively evaluate the extracted features. The proposed model was evaluated using experimental bearing signals simulating various operating states. The results proved that the features, extracted and evaluated by the VSDAE, allowed the recognition of the operating states of the examined bearings.

A Remotely Controlled Oropharyngeal Swab Sampling Robot and Its Application in COVID-19 Prevention

Oropharyngeal swab sampling is the major viral nucleic acid detection method to diagnose COVID-19. Medical staff exposes themselves to the respiratory secretions of patients, which makes them vulnerable to infection. To protect medical staff, we summarize the clinical requirements for robot into five considerations (standardization, ergonomics, safety, isolation, and task allocation) and developed a remotely operated oropharyngeal swab sampling robot. With robot assistance, spatial isolation between medical staff and the patients can be achieved. We designed a hybrid force/position control scheme for the sampling robot to achieve intuitive operation and stable contact force. The experiment results on phantom tissue show that the sampling robot can achieve intuitive operation and stable contact on the soft posterior pharyngeal. Clinical trials for 20 volunteers and 2 patients diagnosed with COVID-19 are carried out. The results of the clinical trial indicated that the sampling robot can collect samples stably and effectively, and the contact force is gentler and more uniform. For two patients diagnosed with COVID-19, the robot sampling results are consistent with manual sampling.