Robot Software Research Articles

129 Neuroimaging Analysis of Bilateral Thalamic Delivery for Gene Therapy

INTRODUCTION: Axonal transport from the thalamus (an integrative hub for the entire cortex) has been shown to facilitate widespread gene/protein delivery. Here, we report our neuroimaging experience with bilateral thalamic convection-enhanced delivery of adeno-associated virus (AAV) vectors for GM2 gangliosidoses. METHODS: Magnetic resonance imaging (MRI) of eight pediatric patients who underwent bilateral thalamic HEXA/HEXB delivery were retrospectively reviewed. Quantitative three-dimensional volumetric analyses of MRI thalamic signals were used to establish volume of distribution (Vd) versus volume of infusion (Vi). The distance of cannula placement within the thalamus was calculated and validated using the numbers used in the intraoperative ROSA robotic software. Backflow and leakage into surrounding structures were also analyzed. RESULTS: Fourteen thalamic injection volumes were considered in the final analysis. Calculated volume of thalamic infusate signal was up to 43.8% (mean = 21.3±13.3) of the thalamic volume. The Vd/Vi ratio ranged from 0.4-2.7 (mean = 1.9±0.7), depending on infusate volume. Diffusate shape was round to slightly ellipsoid in all patients. Backflow and leakage were encountered in 14.3% and 12.5%, respectively, of thalamic injections. CONCLUSIONS: This study provides the first in-human quantitative MRI data for intrathalamic infusion. The ideal location for the cannula tip was determined to be between the mediodorsal and lateral dorsal nuclei and the ideal trajectory keeps all of the cannula steps within the thalamic boundaries. We also compare these data to published NHP and our own NHP and sheep data. Overall, the Vd/Vi ratios are lower in human subjects (∼2) than in animal subjects (∼3). We hypothesize that this may be due in part to species specific differences in displacement of extracellular fluid versus infusion volume.

ROBUST: 221 bugs in the Robot Operating System

As robotic systems such as autonomous cars and delivery drones assume greater roles and responsibilities within society, the likelihood and impact of catastrophic software failure within those systems is increased. To aid researchers in the development of new methods to measure and assure the safety and quality of robotics software, we systematically curated a dataset of 221 bugs across 7 popular and diverse software systems implemented via the Robot Operating System (ROS). We produce historically accurate recreations of each of the 221 defective software versions in the form of Docker images, and use a grounded theory approach to examine and categorize their corresponding faults, failures, and fixes. Finally, we reflect on the implications of our findings and outline future research directions for the community.

ТЯГОВЫЕ РАСЧЕТЫ С УЧЕТОМ ДОПОЛНИТЕЛЬНЫХ ДАННЫХ

The article discusses the technological aspects of automated adjustment of standard train schedules using software robots. The information environment and existing technology for main-taining standard freight train schedules are considered. Information is provided on the implemen-tation of robotic process automation in corporate information systems operated in traffic control directorates. The stages and results of automating the adjustment of standard train schedules using software robots are considered. A generalized diagram of the process of adjusting standard train schedules using a software robot and a special data converter is presented. A fragment of the robot code for uploading the standard schedule into the Elbrus hardware and software complex is given. The issues of using Python programming language libraries to automate processes are considered. An assessment was made of the effectiveness of using software robots to adjust standard sched-ules. The possibilities of joint robotic and intelligent automation for adjusting train schedules are considered.

ТЕХНОЛОГИЯ АВТОМАТИЗИРОВАННОЙ КОРРЕКТИРОВКИ НОРМАТИВНЫХ ГРАФИКОВ ДВИЖЕНИЯ ПОЕЗДОВ С ПРИМЕНЕНИЕМ ПРОГРАММНЫХ РОБОТОВ

The article discusses the technological aspects of automated adjustment of standard train schedules using software robots. The information environment and existing technology for main-taining standard freight train schedules are considered. Information is provided on the implemen-tation of robotic process automation in corporate information systems operated in traffic control directorates. The stages and results of automating the adjustment of standard train schedules using software robots are considered. A generalized diagram of the process of adjusting standard train schedules using a software robot and a special data converter is presented. A fragment of the robot code for uploading the standard schedule into the Elbrus hardware and software complex is given. The issues of using Python programming language libraries to automate processes are considered. An assessment was made of the effectiveness of using software robots to adjust standard sched-ules. The possibilities of joint robotic and intelligent automation for adjusting train schedules are considered.

Automating the Audit of Electronic Invoices With a Software Robot

Taiwan’s Chi Mei Medical Center has completed four challenges mentioned in published robotic process automation (RPA) researches including automating a dynamic process, designing feasible human-robot collaboration, incorporating with other emerging technologies, and bringing positive business impacts. Its executives called a committee to implement the electronic invoicing. This implementation includes the creation of a software robot to download automatically cloud electronic invoice (E-invoice) data from Taiwan’s E-invoice platform and detect the inconsistency between them and on-premise data. This bot operates when internal auditors are off their office. They satisfied this software robot since the remaining work is only verifying the resulting inconsistency. The Chi Mei Medical Center measured the time and costs before and after adopting software robots to audit E-invoice; consequently, it welcomed more bots automating other business processes. In conclusion, integrating a software robot with other emerging technologies mitigates the possible errors provided by this bot. A good human-robot collaboration relies on the consideration of human perspective in choosing RPA tasks. Free bot creators are sufficient to verify that automating a business process using a bot is a reasonable investment.

Design and Implementation of a UMLRPAsec-Extension for Robotic Process Automation

Ensuring RPA (robotic process automation) security is a critical aspect when developing and operating automated software robots. One of the key steps for developing secure software robots is the design stage: the identification and specification of the requirements for the security of the system, the description of system precedents, the interaction between the classes involved in the robot being created, etc. Designs using security-oriented formal modeling languages, such as the UMLsec extension of UML, involve not only a visual representation of diagrams but also the possibility to focus the attention on security issues. However, currently, in the scientific community, there is no possibility of using stereotypes specialized for robots—a mechanism for expanding the unified modeling language that would explicitly reflect a specific problem in the subject area. In this article, we propose that the UMLRPAsec-extension for RPA can be used to model security in the RPA context.

The Rise of Robotic Process Automation in the Banking Sector: Streamlining Operations and Improving Efficiency

Robot Process Automation (RPA) is a type of business process automation that relies on software robots (bots) or artificial intelligence (AI) agents. This phenomenon is sometimes denoted as software robotics, which should not be conflated with robot software. This study investigates the increasing prevalence of RPA across several sectors, with a specific focus on its use in back-office functions. RPA software, exemplified by platforms like Blue Prism, Automation Anywhere, and UiPath, replicates human-computer interactions in order to automate operations that are repetitive and governed by predefined rules. This technology offers many advantages, including cost reduction, mistake minimization, and risk elimination. This research investigates many domains in which RPA may be used, including credible business transformation, content migrations, web crawling/OSINT, and IT department enablement. Additionally, it emphasizes the significant responsibilities within RPA operations, including process architects, technologists, and personnel involved in continuous support and maintenance. The study includes case studies conducted within the banking industry, which demonstrate the potential of RPA in augmenting both customer happiness and productivity. The market report anticipates substantial expansion in the market for RPA software, whereby industry leaders such as UiPath, Automation Anywhere, and Blue Prism are expected to play a dominant role.

Blockchain-Based Smart Contract and Edge AI Applied in a Multirobot System: An Approach

Mining exploration is a common use case in Industry 4.0, which requires robots to work collaboratively to achieve desired goals. In this context, creating and orchestrating software for robotics is often a difficult task.

ВИКОРИСТАННЯ RPA СИСТЕМ ДЛЯ РОБОТИЗАЦІЇ ОБЛІКОВИХ ПРОЦЕСІВ НА ПІДРИЄМСТВАХ

The article explores Robotic Process Automation (RPA) as a technological solution that enables end-users to program or train software robots to perform various operations such as data processing, system interaction, and office tasks. It identifies typical office operations that can be automated using RPA and emphasizes that accounting processes can be effectively automated using robotic software agents. Key areas of accounting process automation are identified, including period closing, reporting, accounts receivable and payable, cash management, general ledger management, inventory, and others. Implementation cases of RPA from various sectors such as technology, printing, and manufacturing have shown significant positive results, including reduced processing time, cost savings, and improved efficiency and accuracy of processes. It is highlighted that the most frequently chosen processes for RPA are purchasing and selling and internal reporting, characterized by routine nature and lack of need for complex decisions. Automating such processes leads to significant productivity and accuracy improvements in accounting. The automation of processing incoming tax invoices is discussed. The benefits of automating accounting are examined, including reduced error risk, increased efficiency, time and resource savings, accuracy and compliance assurance, enhanced analytics, improved process management, greater visibility of results, geographical and cultural independence, and positive impact on employees. Preconditions, challenges, and risks affecting the expected outcome of RPA automation are analyzed. Key aspects to consider when implementing RPA include process design, compatibility with existing IT infrastructure, data security and confidentiality, support and maintenance, as well as task limitations.

Robotic safe adaptation in unprecedented situations: the RoboSAPIENS project

Abstract The robots of tomorrow should be endowed with the ability to adapt to drastic and unpredicted changes in their environment and interactions with humans. Such adaptations, however, cannot be boundless: the robot must stay trustworthy. So, the adaptations should not be just a recovery into a degraded functionality. Instead, they must be true adaptations: the robot must change its behaviour while maintaining or even increasing its expected performance and staying at least as safe and robust as before. The RoboSAPIENS project will focus on autonomous robotic software adaptations and will lay the foundations for ensuring that they are carried out in an intrinsically trustworthy, safe and efficient manner, thereby reconciling open-ended self-adaptation with safety by design. RoboSAPIENS will transform these foundations into ‘first time right’-design tools and platforms and will validate and demonstrate them.

ОРГАНИЗАЦИЯ АВТОМАТИЧЕСКОГО ВЗАИМОДЕЙСТВИЯ УПРАВЛЯЮЩЕЙ ПЛАТФОРМЫ С ИНТЕГРАЛЬНОЙ МАТЕМАТИЧЕСКОЙ СРЕДОЙ

A block diagram and technology for controlling an unstable dynamic system through a given control platform using a software robot directly from the integrated environment of its development are proposed. Essentially, we are talking about creating an MMI (machine-machine interface) type interface that allows you to quickly manage complex, rapidly changing processes from the programming environment. At the same time, it is assumed that there is some automated control system containing its own control platform through which control signals will be transmitted from the software development environment to the control system of a non-stationary object. Special attention is paid to solving the problem of noise immunity of control, implemented through the use of technologies for controlling the passage of commands from the software environment into the control system.

A screenshot-based task mining framework for disclosing the drivers behind variable human actions

Robotic Process Automation (RPA) enables subject matter experts to use the graphical user interface as a means to automate and integrate systems. This is a fast method to automate repetitive, mundane tasks. To avoid constructing a software robot from scratch, Task Mining approaches can be used to monitor human behavior through a series of timestamped events, such as mouse clicks and keystrokes. From a so-called User Interface log (UI Log), it is possible to automatically discover the process model behind this behavior. However, when the discovered process model shows different process variants, it is hard to determine what drives a human’s decision to execute one variant over the other. Existing approaches do analyze the UI Log in search for the underlying rules, but neglect what can be seen on the screen. As a result, a major part of the human decision-making remains hidden. To address this gap, this paper describes a Task Mining framework that uses the screenshot of each event in the UI Log as an additional source of information. From such an enriched UI Log, by using image-processing techniques and Machine Learning algorithms, a decision tree is created, which offers a more complete explanation of the human decision-making process. The presented framework can express the decision tree graphically, explicitly identifying which elements in the screenshots are relevant to make the decision. The framework has been evaluated through a case study that involves a process with real-life screenshots. The results indicate a satisfactorily high accuracy of the overall approach, even if a small UI Log is used. The evaluation also identifies challenges for applying the framework in a real-life setting when a high density of interface elements is present.

Online advance respiration prediction model for percutaneous puncture robotics.

Surgical robots have significant research value and clinical significance in the field of percutaneous punctures. There have been numerous studies on ultrasound-guided percutaneous surgical robots; however, addressing the respiratory compensation problem of deep punctures remains a significant obstacle. Herein we propose a robotic system for percutaneous puncture with respiratory compensation. We proposed an online advance respiratory prediction model based on Bidirectional Gate Recurrent Unit (Bi-GRU) for the respiratory prediction requirements of surgical robot systems. By analyzing the main factors governing the accuracy of the respiratory motion prediction models, various parameters of the online advance prediction model were optimized. Subsequently, we integrated and developed ultrasound-guided percutaneous puncture robot software and a hardware platform to implement respiratory compensation, thus verifying the effectiveness and reliability of various key technologies in the system. The proposed respiratory prediction model has a significantly reduced update time, with an average root mean square error (RMSE) of less than 0.4mm. This represents a reduction of ~ 20% compared to the online training long short-term memory(LSTM). By conducting puncture experiments based on a respiratory phantom, the average puncture error was 2.71 ± 0.65mm and the average single-round puncture time was 65.00 ± 6.67s. Herein we proposed and optimized an online training respiratory prediction network model based on Bi-GRU. The stability and reliability of this system are verified by conducting puncture experiments on a respiratory phantom.

Development and simulation of the Feed Pusher Robot software and hardware system for the maintenance of the feed table at livestock facilities

BACKGROUND: Analysis of trends in the development of industrial technologies in the field of agriculture showed that manufacturers of technological equipment used on farms turn to robotics to exclude human labor when performing labor-intensive cyclical operations that are accompanied by a high degree of tension. To perform operations for the preparation and distribution of feed on a farm, maintenance of the feed table, as well as for manure harvesting, it is necessary to use a wheeled robotic platform with an automatic positioning system.
 AIMS: Development and testing of the software and hardware system of the Feed Pusher robot for the autonomous execution of operations for the maintenance of the feed table at livestock facilities.
 METHODS: Wheeled robot motion simulation, as well as a mathematical description of the kinematic and dynamic properties of the wheeled robot motion was carried out using the MATLAB software and the Simscape library and the Simulink application. The Figma graphic design software was used to develop layouts of mobile software interfaces for the wheeled robot remote control.
 RESULTS: During the wheeled robot motion simulation, direct and inverse kinematics problems were solved, consisting in finding theω1,ω2, vectors with the input parameters x0,y0,φ0,x,y,φ, as well as the final angle of the path (relative to the horizontal). Layouts of the robot remote control software interfaces have been developed, as well as the frontend and backend development of the program adapted to the use at a smartphone has been carried out. The testing of the wheeled robot was carried out at a livestock facility, during the maintenance of the feed table and the simultaneous execution of operations to push the feed to the fence and dosing of feed additives.
 CONCLUSIONS: The practical value of the research lies in the possibility of using the results of the wheeled robot motion simulation to adjust the operation of the automatic positioning system. At the same time, the farmer using the proposed Feed Pusher robot will ensure an increase in the technological efficiency of cattle keeping, in particular dairy cattle, with an increase in milk yields up to 1 liter per day per head, which was determined during the tests on the farm.

ROS2 Real-time Performance Optimization and Evaluation

Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception, force interaction, spatial obstacle avoidance, and motion planning. To ensure the reliability and determinism of system execution, a flexible real-time control system architecture and interaction algorithm are required. The ROS framework was designed to improve the reusability of robotic software development by providing a distributed structure, hardware abstraction, message-passing mechanism, and application prototypes. Rich ecosystems for robotic development have been built around ROS1 and ROS2 architectures based on the Linux system. However, because of the fairness scheduling principle of the default Linux system design and the complexity of the kernel, the system does not have real-time computing. To achieve a balance between real-time and non-real-time computing, this paper uses the transmission mechanism of ROS2, combines it with the scheduling mechanism of the Linux operating system, and uses Preempt_RT to enhance the real-time computing of ROS1 and ROS2. The real-time performance evaluation of ROS1 and ROS2 is conducted from multiple perspectives, including throughput, transmission mode, QoS service quality, frequency, number of subscription nodes and EtherCAT master. This paper makes two significant contributions: firstly, it employs Preempt_RT to optimize the native ROS2 system, effectively enhancing the real-time performance of native ROS2 message transmission; secondly, it conducts a comprehensive evaluation of the real-time performance of both native and optimized ROS2 systems. This comparison elucidates the benefits of the optimized ROS2 architecture regarding real-time performance, with results vividly demonstrated through illustrative figures.

Towards Efficient Robotic Software Development by Reusing Behavior Tree Structures for Task Planning Paradigms

Towards Efficient Robotic Software Development by Reusing Behavior Tree Structures for Task Planning Paradigms

Pelatihan Robot Soccer Bagi Siswa-Siswi SMKN 4 Kota Serang

In the era of the Merdeka Curriculum, Industry 4.0 encompasses online learning, data analysis, artificial intelligence, the Internet of Things, digital skills development, project-based learning, and innovation. This enables a more personalized, efficient, and relevant education, while prioritizing equal access to technology and student data security and privacy. Community service in this context aims to provide introduction and training packaged in the form of a one-day workshop to attract the interest and talents of students at SMKN 4 Kota Serang to the basics of robotics, hardware components, software, as well as the design of hardware and software for soccer robots. The outcome of this activity is that students are able to understand the basic components, programming concepts of soccer robots, and can assemble a soccer robot module effectively and operate it. Many students are enthusiastic about this activity and express hope that it can continue so that a new robotics team can be formed at SMKN 4 Kota Serang, preparing them for upcoming robot competition championships.

Computer Vision Assisted Real-Time Bird Eye Chili Classification Using YOLO V5 Framework

Computer vision-based classification systems have become increasingly popular in the agricultural industry in recent years. This paper proposes a computer vision-assisted bird eye chili or 'kantahri mulaku' classification framework using the You Only Look Once V5 (YOLO V5) object detection model. Automated sorting systems based on computer vision can accurately identify and classify chilies based on attributes such as size, shape, colour, and texture. The dataset for the research consists of images of bird-eye chilies in different positions and backgrounds. The model was trained using this dataset, and it could correctly identify and categorize bird-eye chili. The chilies was then picked up by a robot manipulator and sorted by ripeness. Bird-eye chili images captured in real agricultural situations have used to assess the effectiveness of the suggested framework. Images of red and green chili was taken from above using a high-resolution Raspberry pi 4B camera attached to a custom-built 3-degrees-of-freedom (DoF) robot arm. We used public and real-time images to train the YOLO algorithm on photographs of bird-eye chili captured in real-time. As the robot arm goes around the chili plants, this model is connected with the robot's software control system to allow real-time detection and localization of the chili's. By automating bird-eye chili crop monitoring and management, this system has the potential to significantly contribute to the growth and viability of the agricultural sector. We got a mAP of 0.94 and an average accuracy of 0.90 with the suggested method. Using a robotic manipulator for chili grading improves productivity and reduces human error compared to traditional methods. To test the robustness of the YOLO V5 framework, it has implemented on the Raspberry pi 4B graphical processing unit (GPU) computer.

Scheduling Dynamic Software Updates in Mobile Robots

We present NeRTA ( Ne xt R elease T ime A nalysis), a technique to enable dynamic software updates for low-level control software of mobile robots. Dynamic software updates enable software correction and evolution during system operation. In mobile robotics, they are crucial to resolve software defects without interrupting system operation or to enable on-the-fly extensions. Low-level control software for mobile robots, however, is time sensitive and runs on resource-constrained hardware with no operating system support. To minimize the impact of the update process, NeRTA safely schedules updates during times when the computing unit would otherwise be idle. It does so by utilizing information from the existing scheduling algorithm without impacting its operation. As such, NeRTA works orthogonal to the existing scheduler, retaining the existing platform-specific optimizations and fine-tuning, and may simply operate as a plug-in component. To enable larger dynamic updates, we further conceive an additional mechanism called bounded reactive control and apply mixed-criticality concepts. The former cautiously reduces the overall control frequency, whereas the latter excludes less critical tasks from NeRTA processing. Their use increases the available idle times. We combine real-world experiments on embedded hardware with simulations to evaluate NeRTA. Our experimental evaluation shows that the difference between NeRTA’s estimated idle times and the measured idle times is less than 15% in more than three-quarters of the samples. The combined effect of bounded reactive control and mixed-criticality concepts results in a 150+% increase in available idle times. We also show that the processing overhead of NeRTA and of the additional mechanisms is essentially negligible.

Software Engineering Education for Technical Engineering Degrees: A Comparison With the Needs of Robotics Software Engineering Education

Software Engineering Education for Technical Engineering Degrees: A Comparison With the Needs of Robotics Software Engineering Education