Robot Software Research Articles

Performance analysis on automating the PDF download process using Robotics Process Automation

Many people download one or two files from the internet and it does not take ' much time to download them. What if there is a need for more number of files. For that problem RPA could be the solution. Robotic process automation (or RPA) is a form of business process automation technology based on metaphorical software robots (bots) or on artificial intelligence (AI)/digital workers. The main objective of this paper is to download 100 random pdf files from the internet using excel, csv and datatable automations in Uipath and compare them with the manual way of downloading and finding the most efficient way of downloading the large number of files.

Development of Intelligent Robotic Process Automation: A Utility Case Study in Brazil

Robotic Process Automation (RPA) refers to process automation applications of traditional Information Technologies based on robot software with the ability to capture and interpret the specific processes of organizations. Studies show that RPAs are able to reduce resources and optimize processes effectively in relation to customers. Some of these call center business processes deal with customers most likely to complain; therefore, a “Proactive Notification” robot was developed to classify these types of customers to be prioritized. This robot defines the creation of an RPA architecture for proactive notifications applied to an electric company in Brazil. The methodology used for the development of this project consisted of data management, predictive models, and peripheral components for sending SMS and making calls. It was tested against all customers in 40 cities (two states) and the model considers the historical basis of 3 years of occurrences to predict customers with a high probability of filing a complaint due to power failure. The results show that customers who were called for this type of problem did not call the call center again to complain, suggesting positive acceptance of the robot. In conclusion, the robot presented herein is capable of making proactive notifications with high precision to customers with the highest probability of complaints, predicting possible problems.

Minimizing the number of robots required for a Robotic Process Automation (RPA) problem

Robotic Process Automation (RPA) is used in various fields of human activity in order to implement faster and more secure processes through a reduction in the risks or errors but also an increase in the productivity rates. The increase of its use and importance calls for evermore efficient solution methods for this problem. In this paper, the RPA is addressed in the context of a financial institution. The problem consists in assigning transactions to software robots, where each transaction type has a different clearance date and a different processing time. First, four heuristics are used to compute an upper bound on the number of required software robots. Then, this bound is given as a parameter to an integer linear program, which is used to assign the transactions to the different robots. The quality of the solutions is assessed by an extensive experimental study on a set of 39,000 instances. The results show that two heuristics outperform the others and allow for a faster resolution by the integer linear program which in turn finds the optimal solution for most of the instances within a timeout of 60 seconds.

How software robots can facilitate the procurement process? A case study of Siemens in the Czech Republic

How software robots can facilitate the procurement process? A case study of Siemens in the Czech Republic

Robotic Process Automation Extended with Artificial Intelligence Techniques in Power Distribution Utilities

HIGHLIGHTS In Power Distribution Utilities the management of power meters is critical. Power meters management can be very optimized using software robots. The use of RPA technology is a key aspect for Digital Transformation. The association of RPA and AI is feasible and strategic for any company.

SmartTS: A Component-Based and Model-Driven Approach to Software Testing in Robotic Software Ecosystem

Validating the behaviour of commercial off-the-shelf components and of interactions between them is a complex, and often a manual task. Treated like any other software product, a software component for a robot system is often tested only by the component developer. Test sets and results are often not available to the system builder, who may need to verify functional and non-functional claims made by the component. Availability of test records is key in establishing compliance and thus selection of the most suitable components for system composition. To provide empirically verifiable test records consistent with a component’s claims would greatly improve the overall safety and dependability of robotic software systems in open-ended environments. Addi-tionally, a test and validation suite for a system built from the model package of that system empirically codifies its behavioural claims. In this paper, we present the “SmartTS methodology”: A component-based and model-driven approach to generate model-bound test-suites for software components and systems. SmartTS methodology and tooling are not restricted to the robotics domain. The core contribution of SmartTS is support for test and validation suites derived from the model packages of components and systems. The test-suites in SmartTS are tightly bound to an application domain’s data and service models as defined in the RobMoSys (EU H2020 project) compliant SmartMDSD toolchain. SmartTS does not break component encapsulation for system builders while providing them complete access to the way that component is tested and simulated.

Discovering social bots on Twitter: a thematic review

The onset of online social networks (OSN) like Twitter became a predominant platform for social expression and public relations. Twitter had 330 million monthly active users by the year 2019. With the gain in popularity, the ratio of virulent and automated accounts has also increased. It is estimated that 48 million of its functioning accounts are bots. Precisely, Twitter bots or Sybil accounts are kinds of automated web robot software that regulate activities like the tweet, retweet, like or follow via Twitter API. These bots misguide and delude genuine users by spreading spurious content. Hence, uncovering malicious bots from authentic users is obligatory to ensure a safe environment on Twitter. In this paper, the nature of Twitter bots and features of bot detection are discussed with their efficiency. Various bot detection approaches are classified based on the attributes and techniques used. Strong and weak aspects of distinct features and techniques are discussed. Key challenges and future research directions in detecting social bots are also presented. Special reference has been emphasised to contemporary emerging trends.

Robot-guided Ventriculoperitoneal Shunt in Slit-like Ventricles.

Ventriculoperitoneal shunt (VPS) is the most common procedure used in the management of hydrocephalus regardless of the etiology. The standard free-hand technique is used for the placement of VPS in patients with enlarged ventricles. In patients with very small ventricles, CSF access through ventriculostomy becomes challenging and free-hand technique may be associated with high failure rates. In these situations, stereotactic-guided VPS becomes very useful. To validate and describe the technique of robotic-guided VPS in cases with very small ventricles. Three patients underwent VPS with robotic guidance between 2016 and 2019. One patient with a diagnosis of occipital meningocele, who later developed recalcitrant CSF leak from the operative site, and two other patients were diagnosed with idiopathic intracranial hypertension (IIH). Plain CT brain with 1-mm slice thickness acquired prior to the surgery was uploaded into the ROSA machine (Zimmer Biomet Warsaw, Indiana). The trajectory for the VPS is created on the robotic software presurgery. The patient is placed in the supine position with head turned to the side contralateral to VPS insertion and fixed with Mayfield clamp. Registration of the patient is done with the robot. The placement of the VPS is commenced with the robotic arm in the predetermined trajectory. Ventricle was hit in a single attempt in all the cases. CSF leak stopped in the case with meningocele; headache, and visual acuity improved in both the cases of IIH. Robotic-guidance provides a safe and accurate method of VPS placement even in the presence of slit-like ventricles.

Remote Monitoring of Heart Patients Using Robotic Process Automation (RPA)

After the age of 60 years or older many people are diagnosed with heart related issues to follow up older patients, bedridden, who needs maximum care at their homes implementation of phone monitoring becomes necessary. According to study many heart patients are supposed to have a regular check up to keep a track on their physiological data. Health care is a ground that is rapidly developing in services and technology. A recent development in this region is remote monitoring of patients which has many benefits in a fast-aging world population with increasing health complications. Sensors are used to monitor essentials or vital requirements such as heartbeat, blood pressure, temperature, blood glucose level and many more. Remote monitoring varies for every age group and every aspect. During pandemic times its difficult for many of them to move around, thus remote monitoring of patients helps to have a safer and efficient way to monitor them and also saves time. These new technologies can make a contact-less and monitor illness based on the sensor values. To make remote monitoring more efficient automation places a vital role. In health sector, to make any process automated RPA (Robotic process automation) is used. Using the established application software robots automate the process originally performed by human beings. This paper focuses on easy way to monitor patients who are in a distant place, have a regular check-up without visiting the doctor regularly and in case of emergency contact the doctor within no time.

Evaluation of the economic efficiency of implementing software robots in a multi-level management system of a housing and communal services enterprise

Evaluation of the economic efficiency of implementing software robots in a multi-level management system of a housing and communal services enterprise

Proposal of Robot Software Platform with High Sustainability

At present, various robotics competitions are being held, including the Tsukuba Challenge. The purpose of participating in a robotics competition is to confirm what can be done with the current technology and to demonstrate new research results. Participating teams often use open source software (OSS) for path planning and autonomous navigation. OSS is advantageous in facilitating participation in robotics competitions. However, applying it to a new robot is difficult when a new research does not involve OSS. In addition, robot systems do not consist only of OSS, and the burden of developing and maintaining other systems is significant. To solve the above problems, a software platform that allows for the addition of research achievements of individual robots is desired. With such a platform, research elements that have already been developed can be shared without the need to develop a new system. This makes it easier to maintain and manage the system and increase its sustainability.

Iterative improvement in the automatic modular design of robot swarms.

Iterative improvement is an optimization technique that finds frequent application in heuristic optimization, but, to the best of our knowledge, has not yet been adopted in the automatic design of control software for robots. In this work, we investigate iterative improvement in the context of the automatic modular design of control software for robot swarms. In particular, we investigate the optimization of two control architectures: finite-state machines and behavior trees. Finite state machines are a common choice for the control architecture in swarm robotics whereas behavior trees have received less attention so far. We compare three different optimization techniques: iterative improvement, Iterated F-race, and a hybridization of Iterated F-race and iterative improvement. For reference, we include in our study also (i) a design method in which behavior trees are optimized via genetic programming and (ii) EvoStick, a yardstick implementation of the neuro-evolutionary swarm robotics approach. The results indicate that iterative improvement is a viable optimization algorithm in the automatic modular design of control software for robot swarms.

Towards Compositional Verification for Modular Robotic Systems

Software engineering of modular robotic systems is a challenging task, however, verifying that the developed components all behave as they should individually and as a whole presents its own unique set of challenges. In particular, distinct components in a modular robotic system often require different verification techniques to ensure that they behave as expected. Ensuring whole system consistency when individual components are verified using a variety of techniques and formalisms is difficult. This paper discusses how to use compositional verification to integrate the various verification techniques that are applied to modular robotic software, using a First-Order Logic (FOL) contract that captures each component's assumptions and guarantees. These contracts can then be used to guide the verification of the individual components, be it by testing or the use of a formal method. We provide an illustrative example of an autonomous robot used in remote inspection. We also discuss a way of defining confidence for the verification associated with each component.

Thoughts on Modeling [Student's Corner

Discusses the concept of designing descriptive models for software robotics.

Algoritmik İşlemler İçin Derin Öğrenme Tabanlı Regresyon Yaklaşımı: BİST30 Örneği

Today, one of the common uses of artificial intelligence is financial markets. In these markets, which are known as stock market, making price predictions for the future using machine learning and deep learning, making the rise and fall forecasts of indices, sectors and stocks are the main approaches used in this field. In the near future in the financial markets, artificial intelligence based software robots are expected to operate instead of people. For this purpose, learning models are developed by using trend and stock price movements. Validation studies such as accuracy, error value and portfolio simulation are performed to demonstrate the performance of the developed models. In this study, a regression model using deep learning was developed to make adaptive buy-sell operations on the time series consisting of closing prices using data from Borsa İstanbul (BIST). The 2006-2015 range of the BIST30 index was used for training, the 2015-2018 range was used for testing, and the model portfolio value gained 39% on the test data for 694 trading days and the trend direction was estimated with 82% accuracy.

Online Reconfiguration of Distributed Robot Control Systems for Modular Robot Behavior Implementation

The use of autonomous robots in areas that require executing a broad range of different tasks is currently hampered by the high complexity of the software that adapts the robot controller to different situations the robot would face. Current robot software frameworks facilitate implementing controllers for individual tasks with some variability, however, their possibilities for adapting the controllers at runtime are very limited and don’t scale with the requirements of a highly versatile autonomous robot. With the software presented in this paper, the behavior of robots is implemented modularly by composing individual controllers, between which it is possible to switch freely at runtime, since the required transitions are calculated automatically. Thereby the software developer is relieved of the task to manually implement and maintain the transitions between different operational modes of the robot, what largely reduces software complexity for larger amounts of different robot behaviors. The software is realized by a model-based development approach. We will present the metamodels enabling the modeling of the controllers as well as the runtime architecture for the management of the controllers on distributed computation hardware. Furthermore, this paper introduces an algorithm that calculates the transitions between two controllers. A series of technical experiments verifies the choice of the underlying middleware and the performance of online controller reconfiguration. A further experiment demonstrates the applicability of the approach to real robotics applications.

Exploring IR4.0 Strategy in Post COVID-19 Era Through Insights from FDI Inflows

Published research on Industrial Revolution 4.0 (IR4.0) is centered around conceptualization and public policy announcements, staying largely esoteric and under-explored. However, with COVID-19 Lockdowns creating an economic crisis out of a health crisis, particularly in countries such as India and USA, it is likely that the vision of IR4.0 will influence new initiatives and collaborative efforts in a post-COVID-19 world realigning to the new normal. India will put its IR4.0 strategy on fast-track to play a meaningful role in the global supply chain. This paper seeks to extend the research literature by studying the possibility of IR4.0 business opportunities for India by looking at trends in FDI in-flows for the period 2013-14 to 2018-19 and by analyzing the financial management of FDI companies. The paper aims to close the research gap by describing and explaining the industries and countries that are best-fit for India’s IR4.0 ambitions. To achieve this objective, a general linear model with repeated measures is applied to a panel data consisting of yearly count of FDI companies reporting to RBI for the period 2013-14 to 2018-19 across nine industry verticals and from 10 investor countries. The study found that though some industry verticals attract FDI, India is not a manufacturing destination, FDI inflows are fickle and most investor countries do not have a strategic buy-in with India through FDI commitments. The main conclusion is that IR4.0 strategy for India can be based on software development for industrial Internet of Things, Human-Machine interface and robotics software. Also, improving Indian business environment and practices in India should be a part of the post COVID-19 strategy.

The Effects of Educational Robotics Applications on Linear Equations about Algebraic Reasoning

The research aims to investigate the effectiveness of the use of educational robotics applications used in linear equations unit on seventh grade students’ algebraic reasoning. Teaching experiment research design was adopted for the research. In the study, usage of idea o-bot robotics software was taught to six 7th grade students. During the research process, three teaching experiment sessions applied after pretesting. Experiment sessions involved activities such as code writing in the face of problem situations, creating algorithms from the written code, monitoring algorithms in the simulation, and improving the algorithms when the desired result is not achieved. Lastly posttesting was performed. Comparing the pretest and posttest results, the data analyses showed that an observable development has been recorded in the algebraic reasoning skills of students’ due to the fact that there are certain patterns and generalization processes in the developed algorithms. In addition, there has been an improvement in the participants' ability to use, understand and transform multiple representations in scientific process skills and problem solving skills.

EUD-MARS: End-user development of model-driven adaptive robotics software systems

• EUD-MARS supports end-user development of model-driven adaptive robotics software. • EUD-MARS is supported by two tools. • The first tool enables software developers to prepare robot profiles. • The second tool enables end-users to program robots using visual blocks. • Three evaluation studies offered positive indications and insights for future work. Empowering end-users to program robots is becoming more significant. Introducing software engineering principles into end-user programming could improve the quality of the developed software applications. For example, model-driven development improves technology independence and adaptive systems act upon changes in their context of use. However, end-users need to apply such principles in a non-daunting manner and without incurring a steep learning curve. This paper presents EUD-MARS that aims to provide end-users with a simple approach for developing model-driven adaptive robotics software. End-users include people like hobbyists and students who are not professional programmers but are interested in programming robots. EUD-MARS supports robots like hobby drones and educational humanoids that are available for end-users. It offers a tool for software developers and another one for end-users. We evaluated EUD-MARS from three perspectives. First, we used EUD-MARS to program different types of robots and assessed its visual programming language against existing design principles. Second, we asked software developers to use EUD-MARS to configure robots and obtained their feedback on strengths and points for improvement. Third, we observed how end-users explain and develop EUD-MARS programs, and obtained their feedback mainly on understandability, ease of programming, and desirability. These evaluations yielded positive indications of EUD-MARS.

Governance models for robotic process automation: The case of Nordea Bank

The teaching case addresses the governance of robotic process automation at Nordea, a large banking group operating primarily in the Nordic region. Nordea has deployed numerous software robots, for a wide range of business processes, from transaction-processing work and both internal and external reporting all the way to interaction with end users in handling of General Data Protection Regulation (GDPR)-related queries. The scene is set with a meeting where three people discuss the current state of robotic process automation implementation at Nordea: Group Head of Robotics Agnieszka Belowska Gosławska, Head of Robotic Process Automation Operations Piotr Stolarczyk and Acting Head of Robotics Execution Jaroslaw Motylewski. The presentation outlines several governance-related issues and decision points that must be addressed in connection with any deployment of robotic process automation at somewhat large scale within a company. The key issues are related to the software’s development and maintenance, robotic process automation governance and IT infrastructure. Students who have worked through the case should be able to (1) describe archetypal and hybrid governance modes for robotic process automation and (2) evaluate their advantages and disadvantages for solid infrastructure and effective software development and maintenance.