Robot Software Research Articles

RPA Demystified: How Software Robots are Revolutionizing Customer Service

Robotic Process Automation (RPA) is revolutionizing customer service by introducing software robots capable of handling repetitive tasks with unprecedented efficiency and accuracy. This article explores the transformative impact of RPA on customer service operations, drawing parallels with everyday automation experiences to demystify the technology. Through case studies and empirical evidence, we examine how RPA streamlines processes such as data entry, ticket routing, and customer data retrieval, leading to significant improvements in operational efficiency and customer satisfaction. The article addresses common misconceptions about RPA, emphasizing its role as a complement to human workers rather than a replacement. We analyze the synergy between RPA and human customer service representatives, highlighting increased employee productivity and job satisfaction. The article also delves into the future prospects of RPA in customer service, including emerging trends like cognitive RPA, while discussing potential obstacles to widespread adoption and strategies for successful implementation. By presenting a comprehensive overview of RPA's capabilities, benefits, and challenges in the customer service domain, this article provides valuable insights for organizations seeking to enhance their customer service operations through automation.

Optimising acceptability using a user-centred design approach of a robotic software in Industry 4.0: A case study

While robotics and collaborative robotics are becoming increasingly commonplace in industry, operators do not always have full control over these tools. The aim of our robotics software is to give operators back the power to act. A user-centered design approach (UCD, ISO 9241-210, 2019), through four steps, has therefore been put in place within Industry 4.0. The first study aims to understand and specify the context of use through three objectives: to understand the organizational context in which the robotic software is to be designed and implemented, to characterize the end users via primary personas, and to take an interest in the operators' work in order to predict likely future situations and guide the development of the new work tool. The second study aims to specify user requirements using a card sort based on different criteria (ergonomic, UX). The third study presents the design solutions for version 2 of the robotics software. The fourth study evaluates and compares the practical acceptability (UX, usefulness, usability, mental load) and social acceptability (intent to use) of the first and second versions of the robotic software. Our results show, among other things, a significant improvement in acceptability for the second version of the software, suggesting greater acceptability of this technology thanks to the UCD approach.

Development of an automated process for monitoring of amiodarone treatment

Abstract Background Amiodarone treatment requires repeated laboratory evaluations of thyroid and liver function due to risk of side effects during long-term administration. Robotic process automation (RPA) represents the use of software robots to automate repetitive and routine tasks typically performed by humans. Purpose We aimed to develop an RPA using a diagnostic classification algorithm and clinical support system for follow-up of amiodarone treatment. Methods Based on international guidelines and clinical specialist advisory we constructed an RPA which was studied in a test environment in parallel with routine amiodarone treatment. Expert advice was integrated through a series of collaborative workshops, ensuring alignment of the algorithm with current best practices in thyroid and liver disease management. The RPA provided recommendations on the time interval to next laboratory testing and suggestions for patient management to the physician, who was serving as a human-in-the-loop responsible for clinical decisions. Results After iterative improvements the RPA was evaluated against physician orders (n=390 paired orders) without technical failures. The recommended time interval to next follow-up was (mean ± SD) 4.5 ± 2.4 vs. 3.1 ± 1.4 months for RPA vs. physician (p<0.0001). While normal laboratory findings resulted in recommended follow-up in 6 months by the RPA (72.2%) this was only ordered in 9.9% by the physician (Figure). Physicians’ orders clustered between 3-4 months (58.5%). All patients diagnosed with new side effects (n=12) were detected and communicated correctly by the RPA, whereas only 8 were correctly detected and responded to by the physician (Table). Conclusions An automated process constitutes a reliable alternative to the current fully manual management of amiodarone follow-up. It may reduce manual labour, frequency of laboratory testing and detect side effects with increased precision, thereby reducing costs and enhancing patient value. While the RPA shows promise, further research is needed to explore its adaptability to other treatment scenarios.

Accuracy of robotic-assisted surgery for immediate implant placement in posterior teeth: a retrospective case series

BackgroundRobotic computer-assisted implant surgery (r-CAIS) is a revolutionary innovation in oral implantation; however, the clinical feasibility of r-CAIS for immediate implant placement (IIP) in posterior teeth has not been verified. Thus, this study aimed to evaluate the accuracy of r-CAIS for IIP in posterior tooth regions.MethodsPatients with posterior teeth to be extracted and indicated to undergo r-CAIS were evaluated. The patients had positioning markers installed in the oral cavity and underwent cone-beam computed tomography (CBCT). Subsequently, minimally invasive tooth extractions were performed, and an individualised surgical plan was generated in the robotic software. After marker registration, implantation surgery was performed by the robotic arm under the supervision and assistance of the surgeons. Finally, the deviations between the planned and placed implants were evaluated based on preoperative and postoperative CBCT data.ResultsA total of 12 patients were evaluated. No adverse events occurred during the surgery. The mean global coronal, global apical, and angular deviations were 0.46 ± 0.15 mm (95%CI:0.36 to 0.56 mm), 0.46 ± 0.14 mm (95%CI:0.37 to 0.54 mm), and 1.05 ± 0.55° (0.69 to 1.40°), respectively.ConclusionsUnder the limited conditions of this study, the r-CAIS exhibited high accuracy in posterior teeth IIP surgery. Further multicentre randomised controlled studies are required to confirm the feasibility of this technology.

Software architecture-based self-adaptation in robotics

Context:Robotics software architecture-based self-adaptive systems (RSASSs) are robotics systems made robust to runtime uncertainty by adapting their software architectures. The research landscape of RSASS approaches is multidisciplinary and fragmented, with many aspects still unexplored or ineffectively shared among communities involved. Objective:We aim at identifying, classifying, and analyzing the state of the art of existing approaches for RSASSs from the following perspectives: (i) the key characteristics of approaches and (ii) the evaluation strategies applied by researchers. Method:We apply the systematic mapping research method. We selected 37 primary studies via automatic, manual, and snowballing-based search and selection procedures. We rigorously defined and applied a classification framework composed of 32 parameters and synthesize the obtained data to produce a comprehensive overview of the state of the art. Results:This work contributes (i) a rigorously defined classification framework for studies on RSASSs, (ii) a systematic map of the research efforts on RSASSs, (iii) a discussion of emerging findings and implications for future research, and (iv) a publicly available replication package. Conclusion:This study provides a solid evidence-based overview of the state of the art in RSASS approaches. Its results can benefit RSASS researchers at different levels of seniority and involvement in RSASS research.Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board.

Development and validation of a robotic system for milling individualized jawbone cavities in oral and maxillofacial surgery

ObjectivesThis study aimed to develop and validate a robotic system capable of performing accurate and minimally invasive jawbone milling procedures in oral and maxillofacial surgery. MethodsThe robotic hardware system mainly includes a UR5E arm (Universal Robots, Denmark) and the binocular positioning system (FusionTrack 250, Atracsys LLC, Switzerland). The robotic software (Dental Navi 3.0.0, Yakebot Technology Ltd., China) is capable of generating cutting tool paths based on three-dimensional shape description files, typically in the stereolithography format, and selected cutting tool parameters, as well as designing surgical accessories. Fully impacted supernumerary tooth models in the maxilla were fabricated using software and three-dimensional printing. Following the planning of a customized cavity to fully expose the tooth, maxillary bone milling was performed on both the robot and static guide groups (n = 8). After milling, all models underwent scanning for assessment. ResultsIn the experiment with fully buried supernumerary tooth models in the maxilla, the root mean square, translation error, over-removal rate, and maximum distance were significantly smaller in the robot group compared to the static guide group. Moreover, the overlap ratio and Dice coefficient were significantly greater in the robot group. No statistically significant differences were observed between the two groups in terms of the rotation error (P = 0.80) or under-removal rate (P = 0.92). ConclusionsThis study has developed a robotic system for milling individualized jawbone cavities in oral and maxillofacial surgery, and its accuracy has been preliminarily verified to meet clinical requirements. Clinical significanceThe robotic system can achieve precise, minimally invasive, individualized jawbone milling in a variety of oral and maxillofacial surgeries, including tooth autotransplantation, surgical reshaping for zygomatic fibrous dysplasia, removal of fully impacted supernumerary or impacted teeth, and endodontic microsurgery, among other relevant clinical applications.

ROS Gateway: Enhancing ROS Availability across Multiple Network Environments.

As the adoption of large-scale model-based AI grows, the field of robotics is undergoing significant changes. The emergence of cloud robotics, where advanced tasks are offloaded to fog or cloud servers, is gaining attention. However, the widely used Robot Operating System (ROS) does not support communication between robot software across different networks. This paper introduces ROS Gateway, a middleware designed to improve the usability and extend the communication range of ROS in multi-network environments, which is important for processing sensor data in cloud robotics. We detail its structure, protocols, and algorithms, highlighting improvements over traditional ROS configurations. The ROS Gateway efficiently handles high-volume data from advanced sensors such as depth cameras and LiDAR, ensuring reliable transmission. Based on the rosbridge protocol and implemented in Python 3, ROS Gateway is compatible with rosbridge-based tools and runs on both x86 and ARM-based Linux environments. Our experiments show that the ROS Gateway significantly improves performance metrics such as topic rate and delay compared to standard ROS setups. We also provide predictive formulas for topic receive rates to guide the design and deployment of robotic applications using ROS Gateway, supporting performance estimation and system optimization. These enhancements are essential for developing responsive and intelligent robotic systems in dynamic environments.

Timely Quality Problem Resolution in Peer-Production Systems: The Impact of Bots, Policy Citations, and Contributor Experience

Online peer-production systems create value by enabling people to participate in the production of a common good such as an open encyclopedia by building freely on each other’s work. Fixing quality problems in peer production in a timely manner is critical because millions of people rely on peer-produced content for learning and decision making. The longer low-quality content remains in place, the more it can harm the reputation of a peer-production system and diminish the capability of the system to maintain its contributor base. We study different mechanism affecting the timeliness of quality problem resolution in Wikipedia and find that the speedy resolution of quality problems depends on the successful integration of software robots (bots) and the careful calibration of policy citations to the different levels of experience among contributors. Most control mechanisms found in firm-based production do not apply to peer production, and instead, quality control in peer production must leverage the strengths of different contributors and harness the benefits of technological support and adaptive policy frameworks to improve productivity and achieve high-quality outcomes.

Assessment of cantilevered curtain wall system supported by tension rods for an enclosed circular building

Curtain wall systems have undergone significant advancements to meet the evolving architectural requirements and achieve aesthetic appeal and functionality in buildings worldwide. These non-structural enclosures, typically constructed with lightweight materials like glass or metal panels, contribute to the visual appeal of high-rise structures while providing numerous benefits, such as ample natural light and unobstructed views. The current paper focuses on analyzing and designing a cantilevered curtain wall system supported by tension rods for the auditorium façade at a simulation centre. The curtain wall surrounds the entire primary structure of the building, which has a circular layout. The study uses numerical modeling with the Robot software to analyze stresses and deflections in the glass, tension rods, mullions, and transoms while considering a wind load of 1.6 kPa. According to the findings, tempered laminated glass that is 19.52 mm thick satisfies the Ultimate Limit States (ULS) and Serviceability Limit States (SLS). Under the limit states, the Technal system (FM169) reinforced with steel tubes can transfer the design loads. The steel framing system that supports the tension rods and transfers the load of the curtain wall to the main structure is likewise considered safe. The structural integrity of the curtain wall is ensured by the prescribed requirements for the connections, which include a 5 mm fillet weld with a throat thickness of 3.5 mm, 20 mm diameter tension rod (Kin long system), and 8 mm thick MS plates with channel brackets. This research expands the practical application of cantilevered curtain wall systems of buildings with enclosed circular layouts.

A Design Flow Based on Docker and Kubernetes for ROS-based Robotic Software Applications

Human-centered robotic applications are becoming pervasive in the context of robotics and smart manufacturing, and such a pervasiveness is even more expected with the shift to Industry 5.0. The always increasing level of autonomy of modern robotic platforms requires the integration of software applications from different domains to implement artificial intelligence, cognition, and human-robot/robot-robot interaction. Developing and (re)configuring such a multi-domain software to meet functional constraints is a challenging task. Even more challenging is customizing the software to satisfy non-functional requirements such as real-time, reliability, and energy efficiency. In this context, the concept of Edge-Cloud continuum is gaining consensus as a solution to address functional and non-functional constraints in a seamless way. Containerization and orchestration are becoming a standard practice, as they allow for better information flow among different network levels as well as increased modularity in the use of multi-domain software components. Nevertheless, the adoption of such a practice along the design flow, from simulation to the deployment of complex robotic applications by addressing the de facto development standards (e.g., ROS - Robotic Operating System) is still an open problem. We present a design methodology based on Docker and Kubernetes that enables containerization and orchestration of ROS-based robotic SW applications for heterogeneous and hierarchical HW architectures. The methodology aims at (i) integrating and verifying multi-domain components since early in the design flow, (ii) mapping software tasks to containers to minimize the performance and memory footprint overhead, (iii) clustering containers to efficiently distribute load across the edge-cloud architecture by minimizing resource utilization, and (iv) enabling multi-domain verification of functional and non-functional constraints before deployment. The article presents the results obtained with a real case of study, in which the design methodology has been applied to program the mission of a Robotnik RB-Kairos mobile robot in an industrial agile production chain. We have obtained reduced load on the robot’s HW with minimal performance and network overhead, thanks to the optimized distributed system.

Is it feasible to develop a supervised learning algorithm incorporating spinopelvic mobility to predict impingement in patients undergoing total hip arthroplasty?

Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy. We identified nine predictors from an analysis of baseline spinopelvic characteristics and surgical planning parameters. Using fivefold cross-validation, the LGBM achieved 70.2% impingement prediction accuracy. With impingement data, the LGBM estimated direction with 85% accuracy, while the support vector machine (SVM) determined impingement type with 72.9% accuracy. After integrating imaging data with a multilayer perceptron (tabular) and a convolutional neural network (radiograph), the LGBM's prediction was 68.1%. Both combined and LGBM-only had similar impingement direction prediction rates (around 84.5%). This study is a pioneering effort in leveraging AI for impingement prediction in THA, utilizing a comprehensive, real-world clinical dataset. Our machine-learning algorithm demonstrated promising accuracy in predicting impingement, its type, and direction. While the addition of imaging data to our deep-learning algorithm did not boost accuracy, the potential for refined annotations, such as landmark markings, offers avenues for future enhancement. Prior to clinical integration, external validation and larger-scale testing of this algorithm are essential.

About managing the number of simultaneously functioning software robots of different types

Objectives. The study sets out to justify the relevance and investigate approaches for solving the problem of managing the number of simultaneously functioning software robots of various types under conditions of limited computational resources and changes in sets of executable tasks.Methods. A proposed solution is based on models and methods of scenario management, linear programming, inventory management, queuing theory, and machine learning. The described methods are valid for different compositions and preconditions for generating initial data, as well as ensuring the relevance horizons of the obtained solutions.Results. The initial data is obtained via the presented approach for determining the computational resource parameters for operating a single software robot. The resources are determined by analyzing the composition of the software and information services used by an actual software robot. Problem statements and mathematical models are developed for cases involving scenario management and linear programming methods. Methods for real-time management of the number of software robots and their sequential local optimization are proposed based on the abovementioned solution sequences. The developed method for generating statistical data based the results of applying the sequential local optimization method is used to identify deficient and non-deficient computational resources. Some results of working in the multi-functional center of RTU MIREA software robots developed on the Аtоm.RITA platform are outlined.Conclusions. The emerging problem of managing the number of simultaneously operating software robots of various types for cases involving scenario control methods and linear programming is formalized. This problem is relevant in the field of automation of business processes of organizations. The use of mathematical methods for solving this problem opens up opportunities for expanding the functional capabilities of robotic process automation platforms, as well as increasing their economic efficiency to create competitive advantages by optimizing the use of IT infrastructure components.

Timing analysis of processing chains with data refreshing in ROS 2

Robot Operating System (ROS) 2 is currently the most popular framework for robotic software development. Safety-critical robotic software are subject to hard end-to-end timing constraints. A processing chain, composed of an ordered sequence of inter-communicating tasks, is used to describe the sequential steps to complete a certain functionality. Tasks in processing chains communicate via the buffer between them, and the data handling semantics greatly affects end-to-end timing performance. Data refreshing is one of the widely applied data handling semantics. However, limited research has been conducted on the timing performance associated with this type of semantics. This paper presents methods for analyzing the end-to-end timing performance with data refreshing semantics, and formally proves the buffer size configuration to optimize end-to-end latency. Experiments with randomly generated workload and a case study are conducted to evaluate proposed methods.

Application of Software Robots and Deep Learning in Real time Processing of E-commerce Orders

Application of Software Robots and Deep Learning in Real time Processing of E-commerce Orders

Автоматизация процессов в системах дистанционного обучения: современные решения и перспективы

The role of automation in distance learning systems and its impact on educational processes is considered. Current trends in the field of distance education and the role of software robots in improving the effectiveness of the educational process are discussed. The analysis of popular SDS, such as Moodle and Google Classroom, and the prospects for their development using innovative technologies are presented. The article also discusses the problems and possibilities of automating processes in educational institutions.

A rule‐based method to effectively adopt robotic process automation

AbstractRobotic Process Automation (RPA) is an emerging software technology for automating business processes. RPA uses software robots to perform repetitive and error‐prone tasks previously done by human actors quickly and accurately. These robots mimic humans by interacting with existing software applications through user interfaces (UI). The goal of RPA is to relieve employees from repetitive and tedious tasks to increase productivity and to provide better service quality. Yet, despite all the RPA benefits, most organizations fail to adopt RPA. One of the main reasons for the lack of adoption is that organizations are unable to effectively identify the processes that are suitable for RPA. This paper proposes a new method, called Rule‐based robotic process analysis (RRPA), that assists process automation practitioners to classify business processes according to their suitability for RPA. The RRPA method computes a suitability score for RPA using a combination of two RPA goals: (i) the RPA feasibility, which assesses the extent to which the process or the activity lends itself to automation with RPA and (ii) the RPA relevance, which assesses whether the RPA automation is worthwhile. We tested the RRPA method on a set of 13 processes. The results showed that the method is effective at 82.05% and efficient at 76.19%.

Challenges in closing the gap between software and hardware in robotics

Challenges in closing the gap between software and hardware in robotics

Enhancing Informal Education with Robotic Process Automation

Robotic Process Automation (RPA) is a cutting-edge technology that empowers software robots to perform repetitive digital tasks based on predefined rules. Traditionally, these tasks are carried out by humans interacting with various software applications through mouse and keyboard actions. RPA robots excel at emulating human actions with exceptional precision, speed, and consistency. RPA has gained widespread popularity across industries for its capacity to streamline business processes, increase productivity, and reduce operational costs. In educational settings, RPA is becoming an integral part of broader digital transformations. The related work discussed in this paper highlights that RPA is commonly utilized to automate administrative tasks for university staff, teachers, and occasionally students, while its potential applications in the learning process remain largely unexplored. Addressing this research gap, we introduce an innovative approach to leverage RPA in informal learning. Our method focuses on automating the course search process on e-learning platforms. The proposed algorithm includes interaction with platform interface, extraction of essential course details, storing retrieved data, and generating structured reports, all while communicating with various systems. Subsequently, we present a solution developed based on this approach, along with its outcomes, evaluation, and discussion of findings.

Two-Dimensional Versus Three-Dimensional Preoperative Planning in Total Hip Arthroplasty

BackgroundPreoperative planning in total hip arthroplasty (THA) involves utilizing radiographs or advanced imaging modalities, including computerized tomography scans, for precise prediction of implant sizing and positioning. This study aimed to compare 3-dimensional (3D) versus 2-dimensional (2D) preoperative planning in primary THA with respect to key surgical metrics, including restoration of the horizontal and vertical center of rotation (COR), combined offset, and leg length. MethodsThis study included 60 patients undergoing primary THA for symptomatic hip osteoarthritis (OA), randomly allocated to either robotic arm–assisted or conventional THA. Digital 2D templating and 3D planning using the robotic software were performed for all patients. All measurements to evaluate the accuracy of templating methods were conducted on the preoperative computerized tomography scanogram, using the contralateral hip as a reference. Sensitivity analyses explored differences between 2D and 3D planning in patients who had superolateral or medial OA patterns. ResultsCompared to 2D templating, 3D templating was associated with less medialization of the horizontal COR (−1.2 versus −0.2 mm, P = .002) and more accurate restoration of the vertical COR (1.63 versus 0.3 mm, P < .001) with respect to the contralateral side. Furthermore, 3D templating was superior for planned restoration of leg length (+0.23 versus −0.74 mm, P = .019). Sensitivity analyses demonstrated that in patients who had medial OA, 3D planning resulted in less medialization of horizontal COR and less offset reduction. Conversely, in patients who had superolateral OA, there was less lateralization of horizontal COR and less offset increase using 3D planning. Additionally, 3D planning showed superior reproducibility for stem, acetabular cup sizes, and neck angle, while 2D planning often led to smaller stem and cup sizes. ConclusionsOur findings indicated higher accuracy in the planned restoration of native joint mechanics using 3D planning. Additionally, this study highlights distinct variances between the 2 planning methods across different OA pattern subtypes, offering valuable insights for clinicians employing 2D planning.

A containerised approach for multiform robotic applications.

As the area of robotics achieves promising results, there is an increasing need to scale robotic software architectures towards real-world domains. Traditionally, robotic architectures are integrated using common frameworks, such as ROS. Therefore, systems with a uniform structure are produced, making it difficult to integrate third party contributions. Virtualisation technologies can simplify the problem, but their use is uncommon in robotics and general integration procedures are still missing. This paper proposes and evaluates a containerised approach for designing and integrating multiform robotic architectures. Our approach aims at augmenting preexisting architectures by including third party contributions. The integration complexity and computational performance of our approach is benchmarked on the EU H2020 SecondHands robotic architecture. Results demonstrate that our approach grants simplicity and flexibility of setup when compared to a non-virtualised version. The computational overhead of using our approach is negligible as resources were optimally exploited.