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Industrial robotic systems (IRS) consist of industrial robots that automate industrial processes. They accurately perform repetitive tasks, replacing or assisting with dangerous jobs like assembly in the automotive and chemical industries. Failures in these systems can be catastrophic, so it is important to ensure their quality and safety before using them. One way to do this is by applying a software testing process to find faults before they become failures. However, software testing in industrial robotic systems has some challenges. These include differences in perspectives on software testing from people with diverse backgrounds, coordinating and collaborating with diverse teams, and performing software testing within the complex integration inherent in industrial environments. In traditional systems, a well-known development process uses simple, structured sentences in English to facilitate communication between project team members and business stakeholders. This process is called behavior-driven development (BDD), and one of its pillars is the use of templates to write user stories, scenarios, and automated acceptance tests. We propose a software testing (ST) approach called automated acceptance testing for industrial robotic systems (AAT4IRS) that uses natural language to write the features and scenarios to be tested. We evaluated our ST approach through a proof-of-concept, performing a pick-and-place process and applying mutation testing to measure its effectiveness. The results show that the test suites implemented using AAT4IRS were highly effective, with 79% of the generated mutants detected, thus instilling confidence in the robustness of our approach. [ABSTRACT FROM AUTHOR]

Delivering large horizontal controlled forces for long periods with aerial manipulators is not an easy task to accomplish; several factors including disturbances, reaction forces from the on-board arm or actuator's limitations might diminish their horizontal force delivery capabilities. Aiming to mitigate these drawbacks, this paper presents a comprehensive study of the force delivery capabilities of aerial manipulators leveraging the environment. The methodology to evaluate the aforementioned capabilities is the Generalized-Jacobian-based force ellipsoid, which was applied to different types of both free-flying and attached-to-the-environment aerial manipulators. In addition, large controlled force delivery experiments with the mentioned manipulators were conducted on physics-engine-based robotics simulation software. The obtained results categorically demonstrate that aerial manipulators leveraging the environment are capable of delivering larger forces than their free-flying counterparts, which has not been proved in the literature so far in the field of aerial robotics. [ABSTRACT FROM AUTHOR]

This survey introduces 101 new publications on applications of Clifford's geometric algebras (GAs) newly published during 2022 (until mid‐January 2023). The selection of papers is based on a comprehensive search with Dimensions.ai, followed by detailed screening and clustering. Readers will learn about the use of GA for mathematics, computation, surface representations, geometry, image, and signal processing, computing and software, quantum computing, data processing, neural networks, medical science, physics, electric engineering, control and robotics. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Glenoid component positioning is an important and challenging aspect of total shoulder arthroplasty. The use of freehand technique with standard instrumentation or preoperative planning based on 2-dimensional computed tomography (CT) scans provides an opportunity for improvement in terms of component accuracy, precision, and deformity correction. These techniques have produced varying outcomes. Methods: Preoperative planning software (PPS), patient specific instrumentation (PSI), and intraoperative navigation (NAV) have been developed to improve the accuracy of implant placement and deformity correction with the ultimate goals of improved patient outcomes and implant longevity. Literature search was conducted on published and available studies comparing the accuracy of glenoid component placement and improvements in surgical and patient outcomes amongst the aforementioned techniques. Results: PPS, PSI, and NAV have demonstrated improved accuracy over freehand techniques with standard instrumentation. However, data demonstrating the clinical benefit and cost effectiveness of these new technologies are lacking. Discussion: In this paper, we reviewed the evidence available to answer the question of whether or not advanced shoulder arthroplasty technologies have been beneficial and reviewed future technologies in development such as virtual/mixed-reality and robotic assisted shoulder surgery. Level of Evidence: 4. [ABSTRACT FROM AUTHOR]

Current practice in simulation and implementation of robot controllers is usually undertaken with guidance from high-level design diagrams and pseudocode. Thus, no rigorous connection between the design and the development of a robot controller is established. This paper presents a framework for designing robotic controllers with support for automatic generation of executable code and automatic property checking. A state-machine based notation, RoboChart, and a tool (RoboTool) that implements the automatic generation of code and mathematical models from the designed controllers are presented. We demonstrate the application of RoboChart and its related tool through a case study of a robot performing an exploration task. The automatically generated code is platform independent and is used in both simulation and two different physical robotic platforms. Properties are formally checked against the mathematical models generated by RoboTool, and further validated in the actual simulations and physical experiments. The tool not only provides engineers with a way of designing robotic controllers formally but also paves the way for correct implementation of robotic systems. [ABSTRACT FROM AUTHOR]

AI-based technologies are increasingly pervasive in a number of contexts. Our affective and emotional life makes no exception. In this article, we analyze one way in which AI-based technologies can affect them. In particular, our investigation will focus on affective artificial agents, namely AI-powered software or robotic agents designed to interact with us in affectively salient ways. We build upon the existing literature on affective artifacts with the aim of providing an original analysis of affective artificial agents and their distinctive features. We argue that, unlike comparatively low-tech affective artifacts, affective artificial agents display a specific form of agency, which prevents them from being perceived by their users as extensions of their selves. In addition to this, we claim that their functioning crucially depends on the simulation of human-like emotion-driven behavior and requires a distinctive form of transparency—we call it emotional transparency—that might give rise to ethical and normative tensions. [ABSTRACT FROM AUTHOR]

The Geometric Algebra Fulcrum Library (GA-FuL) version 1.0 is introduced in this paper as a comprehensive computational library for geometric algebra (GA) and Clifford algebra (CA), in addition to other classical algebras. As a sophisticated software system, GA-FuL is useful for practical applications requiring numerical or symbolic prototyping, optimized code generation, and geometric visualization. A comprehensive overview of the GA-FuL design is provided, including its core design intentions, data-driven programming characteristics, and extensible layered design. The library is capable of representing and manipulating sparse multivectors of any dimension, scalar kind, or metric signature, including conformal and projective geometric algebras. Several practical and illustrative use cases of the library are provided to highlight its potential for mathematical, scientific, and engineering applications. The metaprogramming code optimization capabilities of GA-FuL are found to be unique among other software systems. This allows for the automated production of highly efficient code, based on powerful geometric modeling formulations provided by geometric algebra. [ABSTRACT FROM AUTHOR]

Belief–desire–intention (BDI) agents are a popular agent architecture. We extend conceptual agent notation (Can)—a BDI programming language with advanced features such as failure recovery and declarative goals—to include probabilistic action outcomes, e.g. to reflect failed actuators, and probabilistic policies, e.g. for probabilistic plan and intention selection. The extension is encoded in Milner's bigraphs. Through application of our BigraphER tool and the PRISM model checker, the probability of success (intention completion) under different probabilistic outcomes and plan/event/intention selection strategies can be investigated and compared. We present a smart manufacturing use case. A significant result is that plan selection has limited effect compared with intention selection. We also see that the impact of action failures can be marginal—even when failure probabilities are large—due to the agent making smarter choices. [ABSTRACT FROM AUTHOR]

Harnessing between a computer-aided design (CAD) and the actual printing of a part is by far the most arduous task for robotic gas metal arc directed energy deposition (GMA-DED). The generation of a suitable scanning strategy to deposit overlapping tracks and successive layers is currently not supported by an organized single source. Three easy-to-use CAD-to-Print approaches-point-based, feature-based and drawing-based-are presented here utilizing the open-source software for robotic GMA-DED. The point-based approach involves the discretization of the CAD model into a set of target points and suitable for linear paths and regular geometry. The feature-based approach involves the generation of the robot scan path by slicing of the CAD model. It can consider both regular and irregular geometries but suitable for linear paths only. The drawing-based approach involves the robot scan paths drawn along the contours of the CAD model and is flexible for both linear and non-linear scanning paths. Although all the three approaches require user intervention, they have the potential for automation. [ABSTRACT FROM AUTHOR]

Software development for robotics applications is still a major challenge that becomes even more complex when considering multi-robot systems (MRSs). Such distributed software has to perform multiple cooperating tasks in a well-coordinated manner to avoid unsatisfactory emerging behavior. This paper provides an approach for programming MRSs at a high abstraction level using the programming language X-Klaim. The computation and communication model of X-Klaim, based on multiple distributed tuple spaces, permits coordinating with the same abstractions and mechanisms both intra- and inter-robot interactions of an MRS. This allows developers to focus on MRS behavior, achieving readable, reusable, and maintainable code. The proposed approach can be used in practice by integrating X-Klaim and the popular robotics framework ROS. We demonstrate the feasibility and effectiveness of our approach by (i) showing how it scales when implementing two warehouse scenarios allowing us to reuse most of the code when passing from the simpler to the more enriched scenario and (ii) presenting the results of a few experiments showing that our code introduces a slightly greater but acceptable latency and consumes less memory than the traditional ROS implementation based on Python code. [ABSTRACT FROM AUTHOR]

Contemporary discourse on information and communication technology suggests that humans and machines are increasingly converging. However, in this article, we argue that for analysts of digital society it is necessary to understand the simultaneity with which humans and machines are both interconnected and separated from one another. Here, we propose to follow and trace human/machine interfacing, i.e. the manifold practices, by which humans and machines become interconnected, by being kept apart. Drawing on theoretical resources from feminist science and technology studies and the philosophy of technology, we extend common 'objective' notions of the interface and propose a performative and ecological framework for human-machine interfacing. We illustrate this framework with two contrasting cases, embodied social robotics and communicative software bots. Social robots denote a rather fragile technology, showing the precariousness of efforts to engender phenomena of human-machine communication. By contrast, communicative software bots can rely on vast digital infrastructures, which create the impression of symmetry between humans and machines by rendering ontological differences invisible. [ABSTRACT FROM AUTHOR]

Robot software development can be considered as a component-driven process, and existing ROS components, such as an ROS node, can be reused to construct robot applications. By reusing the ROS node, the development process of robot software can be significantly accelerated. However, the challenges in reusing ROS nodes primarily lie in the scattered organization of ROS node information. To address this challenge, this paper proposes a method to construct an ROS node knowledge graph (RNKG) based on high-quality open-source robot projects. In order to build a high-quality knowledge graph of ROS nodes, we first constructed a high-quality dataset of open-source robot projects. Since ROS node knowledge can exist in both text and code formats, we initially separated the data in the dataset into code data and text data, and then applied different knowledge extraction methods to extract corresponding entities. Finally, we integrated a series of ROS node knowledge and organized it into a knowledge graph. To validate the effectiveness of the constructed ROS node knowledge graph, we first verified the completeness of the entities and the accuracy of relationships in the knowledge graph. Next, we evaluated the performance of the ROS node knowledge graph in assisting developers with the downstream task of finding ROS nodes. These findings suggest that our proposed method for constructing an ROS node knowledge graph is feasible and demonstrate that the ROS node knowledge graph helps search ROS nodes. [ABSTRACT FROM AUTHOR]

Ensuring the safety, security, robustness, and fault tolerance of advanced robotic systems is essential for various fields, including healthcare, industry, and space. To address these issues, it is necessary to use software testing techniques and standards, similar to those applied in other safety-critical applications. The Robot Operating System (ROS) is a popular choice for developing robotic systems, so it is important to have specialized testing libraries and methods for it. In this study, a novel mutation testing library for ROS was developed and integrated it into the automated/tailored mutation-based software fault injection tool (IM-FIT). IM-FIT is an open-source automated software testing tool that is used to evaluate the software robustness of safety-critical systems using mutation-based tests. The proposed ROSMutation library mutates ROS-specific code snippets (publisher, subscriber, params, services, etc.) in the Python code within ROS-compatible software packages using IM-FIT. We evaluated the effectiveness of the ROSMutation library in two scenarios (basic and advanced), applying it to ROS-compatible code through IM-FIT and measuring its ability to assess the software robustness of ROS-compatible and Python-based software packages. The results showed that the ROSMutation library is effective in evaluating software robustness criteria for ROS-compatible and Python based software. [ABSTRACT FROM AUTHOR]

Robot Operating System 2 (ROS 2) is a robotic software that uses a set of Quality of Service (QoS) policies to manage the quality of robot data transmissions in a network, such as the RELIABLE and KEEP_LAST options. In ROS 2 node communication, the RELIABLE connection guarantees that all message data can be properly sent from the publisher to the subscriber. However, strict reliability is not guaranteed if the RELIABLE connection uses the KEEP_LAST option to transmit the robot data in the publish–subscribe communication. This study aims to analyze the efficiency of local cache, cache control, and QoS balancing optimization to improve ROS 2 node communication when using the RELIABLE and KEEP_LAST options to transmit multi-robot data in Aggregated Robot Processing (ARP) architecture. Our idea in local cache and cache control is to streamline the sensor data output before processing it when the sensor device produces the data with the same value in a row. Furthermore, QoS balancing optimization aims to balance the DEPTH and DEADLINE QoS configuration to determine the rates and buffer size in ROS 2 node communication. This study shows that combining local cache and QoS balancing optimization improves multi-robot data transmission and cooperation in ARP architecture. [ABSTRACT FROM AUTHOR]

This paper describes the design, implementation, and field‐testing of a low‐cost autonomous control system on the Platform for Expanding Autonomous Underwater Vehicles (AUV) exploRation to Longer ranges (PEARL). PEARL is a floating, solar‐powered platform designed as a servicing station for AUVs. This paper describes the field testing of a prototype system currently without the ability to dock and recharge AUVs. In this prototype, autonomous operations are realized through the open‐source MOOS‐IvP marine robotics software running on an embedded architecture including a Raspberry Pi microcomputer, Arduino microcontroller, and onboard inertial measurement unit and GPS sensors. A solar charge controller monitors energy system statistics in real‐time. Field tests included station‐keeping and waypoint missions in a freshwater pond in Orleans, MA. An RMS tracking error of 0.9–2.2 m was achieved during waypoint pattern executions, with an average battery usage of 13% per hour. Net power consumption rate will change due to variations in currents and winds, as well as variations in solar irradiance. The implementation of an autonomous sun‐tracking mode to maximize solar panel flux while station‐keeping is also evaluated. The field testing results will inform the design of a full‐scale PEARL capable of docking with AUVs. This research helps pave the way for autonomous solar‐powered service stations in the ocean that can connect the underwater world with space. [ABSTRACT FROM AUTHOR]

The field of educational technology has made significant strides, offering cost-effective multimedia tools and physical resources to facilitate both formal and informal teaching methods in computer science, with a particular emphasis on the development of computational thinking (CT) and programming skills. However, there is a lack of research focusing on practice-based tasks, such as Internet of Things (IoT) projects, for undergraduate students to demonstrate and program educational robots using digital and physical-supported instructional approaches. Specifically, there have been no studies examining the association between students' learning outcomes and their absorption and need for cognition on different platforms, such as Scratch and LEGO® WeDo. This study aims to provide empirical evidence by comparing the impact of two different platforms commonly used in programming courses to teach undergraduate students how to design, develop, and program IoT projects using educational robots. A quasi-experimental study was carried out to examine whether there were any significant variations in students' CT skills and programming development, as well as to evaluate their learning outcomes with regard to their need for cognition and absorption when they applied their coding expertise to real-world IoT projects. As a point of reference (control condition), twenty students (n = 20) utilized LEGO® WeDo robotics kits and Scratch for coding tasks, which is the most familiar instructional approach. In the intervention approach (experimental condition), thirty-seven students (n = 37) used LEGO® WeDo robotics kits and their software to learn how to code their educational robots. Participants from the latter group learned how to design and demonstrate the program and showed superior CT skills and programming skills development than their counterparts in the control group who used Scratch. Furthermore, the results indicate that students with higher levels of CT skills and programming execution reveal lower absorption but a higher need for cognition in educational robot-supported IoT projects. [ABSTRACT FROM AUTHOR]

This paper presents an efficient method for minimum distance calculation between a robot and its environment and the implementation framework as a tool for the verification of robotic systems' safety. Collision is the most fundamental safety problem in robotic systems. Therefore, robotic system software must be verified to ensure that there are no risks of collision during development and implementation. The online distance tracker (ODT) is intended to provide minimum distances between the robots and their environments for verification of system software to inspect whether it causes a collision risk. The proposed method employs the representations of the robot and its environment with cylinders and an occupancy map. Furthermore, the bounding box approach improves the performance of the minimum distance calculation regarding computational cost. Finally, the method is applied to a realistically simulated twin of the ROKOS, which is an automated robotic inspection cell for quality control of automotive body-in-white and is actively used in the bus manufacturing industry. The simulation results demonstrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents the implementation of an obstacle avoidance algorithm on the UR5e collaborative robot. The algorithm, previously developed and verified in simulation, allows one to modify in real time the trajectory of the manipulator with three different modalities to avoid obstacles. Some test cases with fixed or dynamic obstacles affecting the robot's motion were first simulated and then experimented on. The paper describes the hardware/software architecture of the robotic system: an external controller is realized by a standard PC that communicates with the robot controller by a TCP/IP protocol; algorithms and data processing are executed by Python/Matlab software that guarantees a duty cycle of at least 100 Hz. The error analysis between simulated and real data allows one to conclude that the developed algorithms revealed to be effectively applied to a real robotic system, showing behavior similar to what is expected by simulations. [ABSTRACT FROM AUTHOR]

Software development for robotic systems is traditionally performed based on simulations, manual code implementation, and testing. However, this software development approach can cause safety issues in some scenarios, including multiple robots sharing a workspace. When different robots are executing individual planned tasks, they may collide when not adequately coordinated. Safety problems related to coordination between robots may not be encountered during testing, depending on timing, but may occur during the system's operation. In this case, formal verification methods can provide a more reliable means to ensure the safety of robotic systems. This paper uses the formal method of model checking for the safety verification of multiple industrial robot manipulators with path conflicts. We give comparative results of two model-checking tools applied to a system with two robot manipulators. Whole workflows, from requirement specification to testing, are presented. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper is the second part of a two-part study on promoting the use of Open-Source Software (OSS) in Mechatronics and Robotics Engineering (MRE) education. Part I demonstrated the capabilities and limitations of several popular OSS, namely, Python, Java, Modelica, and GNU Octave, in model simulation and analysis of dynamic systems, through a DC motor example. The DC motor was chosen as a representative of a large class of dynamic systems described by linear differential equations. The perceptions of MRE community members about the OSS and their applications, gathered through an online survey, were also presented in Part I. In this paper, another fundamental pillar of MRE systems development, i.e., controller implementation, is considered. To this end, the OSS above, along with Gazebo, are used to simulate the closed-loop trajectory tracking performance of a 2-DOF robot manipulator, controlled by a PID controller. Robot manipulators represent a broader category of dynamic systems, which are described by nonlinear differential equations. Furthermore, PID controllers are one of the most versatile closed-loop control methodologies which have been established as the industry standard. Showcasing the implementation of this important category of controllers through OSS can promote their use in a wide range of MRE problems and projects. This paper also provides an overview of the potentials, limitations, and challenges regarding the use of each of the above OSS in solving the aforementioned problems. The OSS are increasingly being adapted as industry standard; furthermore, their numerous benefits pose them as a viable option to complement traditional higher education courses along with facilitating online and remote education. Therefore, this two-part paper and the various problems showcased and solved therein aim to pave the way towards further utilization of the OSS in MRE higher education, reaping the wide range of their benefits, and preparing the students for the future workforce. Full scripts of the codes summarized and discussed in this paper, along with Matlab scripts included to enable comparison, are made freely available on the Github repository of this paper. [ABSTRACT FROM AUTHOR]

Autonomous aerospace technology is an innovation activity currently included in NATO’s operation areas having a profound impact on security and defense. SpaceSysLab facility is the new Laboratory from Romania, able to test control algorithms for autonomous missions and to develop hardware (coupling mechanisms, navigation sensors and actuators). This robot-based test lab is used to test, verify and validate the R&D systems. The degree of novelty is expressed by the fact that the SpaceSysLab designed as a SIL+HIL (Software-in-the-Loop+Hard-inthe-Loop) simulator is a combination of hardware and software simulator that can test and verify space robots, autonomous VTOL (Vertical Take-off and Landing) of UAVs on mobile platforms in complex coupling phases. This technology allows hardware/software robotic broadband systems to be controlled by simulating every phase. SpaceSysLab consists of a virtual platform (VP) based on GNC system (guidance, navigation, and control) and an experimental platform (EP) based on a robotic system. This system permits to simulate the meeting and coupling maneuvers of the robots. VP+EP test system is a hybrid simulator, designed to simulate simultaneously the relative dynamics of two motion bodies on relatively short distances in meeting/coupling maneuvers (rendezvous, proximity and docking – RP&D, VTOL). [ABSTRACT FROM AUTHOR]

Most people with motor disabilities use a joystick to control an electric wheelchair. However, those who suffer from multiple sclerosis or amyotrophic lateral sclerosis may require other methods to control an electric wheelchair. This study implements an electroencephalography (EEG)-based brain–computer interface (BCI) system and a steady-state visual evoked potential (SSVEP) to manipulate an electric wheelchair. While operating the human–machine interface, three types of SSVEP scenarios involving a real-time virtual stimulus are displayed on a monitor or mixed reality (MR) goggles to produce the EEG signals. Canonical correlation analysis (CCA) is used to classify the EEG signals into the corresponding class of command and the information transfer rate (ITR) is used to determine the effect. The experimental results show that the proposed SSVEP stimulus generates the EEG signals because of the high classification accuracy of CCA. This is used to control an electric wheelchair along a specific path. Simultaneous localization and mapping (SLAM) is the mapping method that is available in the robotic operating software (ROS) platform that is used for the wheelchair system for this study. [ABSTRACT FROM AUTHOR]

Service robotics involves the design of robots that work in a dynamic and very open environment, usually shared with people. In this scenario, it is very difficult for decision-making processes to be completely closed at design time, and it is necessary to define a certain variability that will be closed at runtime. MAPE-K (Monitor–Analyze–Plan–Execute over a shared Knowledge) loops are a very popular scheme to address this real-time self-adaptation. As stated in their own definition, they include monitoring, analysis, planning, and execution modules, which interact through a knowledge model. As the problems to be solved by the robot can be very complex, it may be necessary for several MAPE loops to coexist simultaneously in the robotic software architecture endowed in the robot. The loops will then need to be coordinated, for which they can use the knowledge model, a representation that will include information about the environment and the robot, but also about the actions being executed. This paper describes the use of a graph-based representation, the Deep State Representation (DSR), as the knowledge component of the MAPE-K scheme applied in robotics. The DSR manages perceptions and actions, and allows for inter- and intra-coordination of MAPE-K loops. The graph is updated at runtime, representing symbolic and geometric information. The scheme has been successfully applied in a retail intralogistics scenario, where a pallet truck robot has to manage roll containers for satisfying requests from human pickers working in the warehouse. [ABSTRACT FROM AUTHOR]

Robotic process automation (RPA) is a technology for office automation to imitate human behaviour when interacting with computers to perform digitized tasks manually, such as opening and closing applications, reading documents, entering data, and sending e-mails. As with any new digital technology answering the question of where to start and what is the right software, is challenging. In the case of RPA, the question of where to start depends on the selection of the business process to be automated and optimized. There are approaches for process selection in research, but they are relatively complex and have not been validated in practice. To fill this gap, we have simplified the process selection method and validated it on a practical example. We also present a simple method to select the appropriate RPA software. The criteria selection and evaluation were done with the Pairwise Comparison and Benefit Value Analysis method. This approach is relatively easy to follow and to apply in practice and thus also closes a gap in applied research. [ABSTRACT FROM AUTHOR]

In this research, we analyzed the content of a practice-based research published in SSCI, ESCI and ERIC indexed journals related to Computational Thinking (CT) between 2019 and 2021. For this purpose, we searched Science Direct, Google Scholar and Web of Science databases and examined 97 papers. We evaluated the papers under the headings of development approaches, learning tools, sub-skills, research groups, measurement tools, and prominent findings. According to the results, while for programming, robotics, Science, Technology, Engineering and Mathematics (STEM), development courses and computer science unplugged approaches were adopted in the development of CT, CT was mostly associated with the field of computer science. Programming and robotics software such as Scratch, Lego Mindstorms, M-Bot, Arduino and Bee-Bot are tools with a block-based coding interface. While there was no consensus on the scope and measurement of CT, CT was generally studied within the framework of abstraction, decomposition, algorithmic thinking, and debugging subskills. CT developments were measured through scales and tests consisting mostly of multiple-choice and open-ended questions. The research focused on primary and secondary school students while it was limited on preschool level. In addition, studies stating that gender is an effective factor in the development of CT in different age groups are in the majority. Whilst trying to integrate CT into courses in schools, the number of development courses for pre-service and in-service teachers is increasing. Within the framework of the results obtained from the research, the differences in the scope, development, measurement, and evaluation of CT are discussed. [ABSTRACT FROM AUTHOR]

Swarm Robotics is inspired by the biological swarms of social insects such as ants and bees, where individuals performing basic tasks give rise to complex behavior. It utilizes a team of cooperating robots to perform tasks more efficiently than possible by isolated robots. In this research, we study the exploration of unknown indoor areas using robots that coordinate with each other. In particular, we implement the Reverse Nearest Neighbor coordination algorithm with certain modifications to account for real-world constraints. The library developed as part of this work provides scripts to help with robotic tasks for exploration and robotic arm control that can be used to set up simulation tools like VREP, without much prior experience thereby lowering the barrier for entry and making the robotics projects more accessible. [ABSTRACT FROM AUTHOR]

A simulation framework based on the open-source robotic software Gazebo and the Robot Operating System is presented for articulated tracked robots, designed for reinforcement-learning-based (RL) control skill acquisition. In particular, it is destined to serve as a research tool in the development and evaluation of methods in the domain of mobility learning for articulated tracked robots, in 3D indoor environments. Its architecture allows to interchange between different RL libraries and algorithm implementations, while learning can be customized to endow specific properties within a control skill. To demonstrate its utility, we focus on the most demanding case of staircase ascent and descent using depth image data, while respecting safety via reward function shaping and incremental, domain randomization-based, end-to-end learning. [ABSTRACT FROM AUTHOR]

A general pneumatic soft gripper is proposed in this paper. Combined with the torque balance theory, the mathematical theoretical model of bending deformation of soft gripper is established based on Yeoh constitutive model and classical differential geometry. Assuming that the pressure in each inner cavity is evenly distributed, the input gas is in an ideal state, which is approximately treated as an isothermal condition, and all orifices experience blocked flow. In addition, compared with the mechanical work of gas, the energy related to gas flow and heat transfer is negligible. The nonlinear mechanical properties of silicone rubber are studied. It is regarded as isotropic and incompressible material, which is characterized by strain energy per unit volume. The material constant coefficients C10 and C20 are determined through the uniaxial tensile test, and the software gripper is simulated on the ABAQUS platform. The bending deformation models of grippers with three different force-bearing cavity structures are analyzed and compared, and the software clamping structure with the bending deformation most in line with the application conditions is selected. The limit input air pressure of the gripper and the situation of enveloping the clamping target object are analyzed. Through the bending deformation experiment, the maximum deformation angle is 72.4°. The relative error between the simulation analysis data and the prediction results of the mathematical model is no more than 3.5%, which verifies the effectiveness of the simulation and the correctness of the mathematical theoretical model of bending deformation. The soft manipulator proposed in this paper has good adaptability to grasping objects of different shapes and sizes. The minimum diameter of the target object that can be clamped is 0.1 mm. It can clamp the object weighing up to 1 kg. It has compact size, light weight, high ductility, and flexibility. [ABSTRACT FROM AUTHOR]

Substantive testing of accounts receivable through confirmations is an established and required audit procedure. However, the technology used to perform portions of this work is evolving. This case exposes students to the testing of accounts receivable while introducing them to audit-related technologies (such as Interactive Data Extraction and Analysis [IDEA] software and robotic process automation [RPA]) used in practice. In this case, students (1) evaluate a client-provided data file, (2) select a sample of customer invoices using IDEA, (3) obtain audit evidence from their firm's RPA software and evaluate the evidence for the identification of exceptions, (4) project any misstatements from the sample to the population, and (5) document their conclusions. This case helps students develop a greater awareness of technologies used in audit practice. The case also allows students to practice skepticism, apply professional judgment, and hone their business writing skills by documenting their results in a professional memo. [ABSTRACT FROM AUTHOR]

In robotized industrial scenarios, the need for efficiency and flexibility is increasing, especially when tasks must be executed in dangerous environments and/or require the simultaneous manipulation of dangerous/fragile objects by multiple heterogeneous robots. However, the underlying hardware and software architecture is typically characterized by constraints imposed by the robots' manufacturers, which complicates their integration and deployment. This work aims to demonstrate that widely used algorithms for robotics, such as interaction control, can be made independent of the hardware architecture, abstraction level, and functionality provided by the low-level proprietary controllers. As a consequence, a robot-independent control framework can be devised, which reduces the time and effort needed to configure the robotic system and adapt it to changing requirements. Robot-agnostic interaction controllers are implemented on top of the Robot Operating System (ROS) and made freely available to the robotic community. Experiments were performed on the Universal Robots UR10 research robot, the Comau Smart-Six industrial robot, and their digital twins, so as to demonstrate that the proposed control algorithms can be easily deployed on different hardware and simulators without reprogramming. [ABSTRACT FROM AUTHOR]

Background: The development of robotic systems has provided an alternative to frame-based stereotactic procedures. The aim of this experimental phantom study was to compare the mechanical accuracy of the Robotic Surgery Assistant (ROSA) and the Leksell stereotactic frame by reducing clinical and procedural factors to a minimum. Methods: To precisely compare mechanical accuracy, a stereotactic system was chosen as reference for both methods. A thin layer CT scan with an acrylic phantom fixed to the frame and a localizer enabling the software to recognize the coordinate system was performed. For each of the five phantom targets, two different trajectories were planned, resulting in 10 trajectories. A series of five repetitions was performed, each time based on a new CT scan. Hence, 50 trajectories were analyzed for each method. X-rays of the final cannula position were fused with the planning data. The coordinates of the target point and the endpoint of the robot- or frame-guided probe were visually determined using the robotic software. The target point error (TPE) was calculated applying the Euclidian distance. The depth deviation along the trajectory and the lateral deviation were separately calculated. Results: Robotics was significantly more accurate, with an arithmetic TPE mean of 0.53 mm (95% CI 0.41–0.55 mm) compared to 0.72 mm (95% CI 0.63–0.8 mm) in stereotaxy (p < 0.05). In robotics, the mean depth deviation along the trajectory was −0.22 mm (95% CI −0.25 to −0.14 mm). The mean lateral deviation was 0.43 mm (95% CI 0.32–0.49 mm). In frame-based stereotaxy, the mean depth deviation amounted to −0.20 mm (95% CI −0.26 to −0.14 mm), the mean lateral deviation to 0.65 mm (95% CI 0.55–0.74 mm). Conclusion: Both the robotic and frame-based approach proved accurate. The robotic procedure showed significantly higher accuracy. For both methods, procedural factors occurring during surgery might have a more relevant impact on overall accuracy. [ABSTRACT FROM AUTHOR]

Unlike conventional software, robotic software suffers from a lack of methods and processes that could systematize and facilitate development. Thus, the application of software engineering techniques is at the heart of current issues in robotics. The work presented in this paper aims to facilitate the development of robotic software and to facilitate communication between experts in the field through the use of software engineering techniques and methods. It proposes RsaML (Robotic Software Architecture Modeling Language), a Domain Specific Modeling Language (DSML) dedicated to robotics, which takes into account the different categories of robotic software architectures and makes it possible to describe the latter independently from the implementation platform. The conceptual model defining the terminology and the hierarchy of concepts used for the description and representation of robotic software architectures in RsaML are presented in this article. RsaML is defined through a meta-model which represents the abstract syntax of the language. The real-time properties of robotic software architectures are identified and included in the meta-model. The use of RsaML is illustrated through several experimental scenarios of the language: the definition of a robotic system and the description of its software architecture, the verification of the semantics of a robotic software architecture, and the modeling of a robotic system whose software architecture does not belong to the usual categories. The support tool used for implementations and experimentation is Eclipse Modeling Framework (EMF). The results of experimentation showed good working of the proposed solution and made it possible to validate the main concepts of the RsaML language. [ABSTRACT FROM AUTHOR]

Due to ligament laxity, bearing dislocation occurs in 1–6% of Oxford Domed Lateral (ODL) replacements with most dislocations occurring medially. Dislocations were studied using a previously built mechanical rig, however testing using the rig was inefficient. The aim of this study was to develop a better tool that was more reliable and efficient. An established robotics software package, the Open Motion Planning Library, was modified to accept the ODL components. Using a robotics path planning algorithm, the mobile bearing was allowed to find a way out from between the femoral and tibial components i.e. to dislocate. Testing assessed a range of clinically relevant positions of the femoral component relative to the tibial component. Dislocations were labelled as medial, lateral, anterior or posterior depending on the dislocation direction. The Distraction to Dislocation (DD) measured the minimum vertical distraction of the femoral component from the tibial component for a dislocation to occur. Results were validated against the mechanical rig. Statistical analysis of medial dislocation showed excellent agreement with an intraclass correlation value of 0.993 (95% CI 0.982–0.998). All DDs from the dislocation analysis tool were within 1 mm of the mechanical rig DDs with results sharing a remarkably similar trend. The robotics dislocation analysis tool output DDs which were marginally higher than the manual mechanical rig: 0.50 mm anteriorly, 0.25 mm posteriorly and 0.50 mm laterally. Medially, the computational DD differed on average by 0.09 mm (stand deviation: 0.2026 mm). Our study describes the development and validation of a novel robotics dislocation analysis tool, which allows mobile bearing dislocation risk quantification. The tool may also be used to improve surgical implantation parameters and to assess new implant designs that aim to reduce the medial dislocation risk to an acceptable level. [ABSTRACT FROM AUTHOR]

Mobile robots operate in various environments (e.g. aquatic, aerial, or terrestrial), they come in many diverse shapes and they are increasingly becoming parts of our lives. The successful engineering of mobile robotics systems demands the interdisciplinary collaboration of experts from different domains, such as mechanical and electrical engineering, artificial intelligence, and systems engineering. Research and industry have tried to tackle this heterogeneity by proposing a multitude of model-driven solutions to engineer the software of mobile robotics systems. However, there is no systematic study of the state of the art in model-driven engineering (MDE) for mobile robotics systems that could guide research or practitioners in finding model-driven solutions and tools to efficiently engineer mobile robotics systems. The paper is contributing to this direction by providing a map of software engineering research in MDE that investigates (1) which types of robots are supported by existing MDE approaches, (2) the types and characteristics of MRSs that are engineered using MDE approaches, (3) a description of how MDE approaches support the engineering of MRSs, (4) how existing MDE approaches are validated, and (5) how tools support existing MDE approaches. We also provide a replication package to assess, extend, and/or replicate the study. The results of this work and the highlighted challenges can guide researchers and practitioners from robotics and software engineering through the research landscape. [ABSTRACT FROM AUTHOR]

The design of robots capable of operating autonomously in changing and unstructured environments, requires using complex software architectures in which, typically, robot engineers manually hard-code adaptation mechanisms allowing the robot to deal with certain situations. As adaptation is closely related with context monitoring, deliberation and actuation, its implementation typically spreads across several architecture components. Therefore, fine-tuning or extending the adaptation logic (e.g., to cope with new contingencies not foreseen at design-time) results in a very expensive and cumbersome process. This paper proposes a novel approach to deal with self-adaptation based on modeling behavior variability at design-time so that the robot can configure it at runtime, according to the contextual information only then available. This approach is supported by a model-based framework allowing robotic engineers to specify (1) the robot behavior variation points (open decision space); (2) the internal and external contextual information available; and (3) the non-functional properties (e.g. safety, performance, or energy consumption) in terms of which the robot Quality-of-Service (QoS) will be measured. Then, from these models, the framework will automatically generate the runtime infrastructure allowing the robot to self-adapt its behavior to achieve the best QoS possible according to its current context. The framework has been validated in two scenarios using two different well-known robotic software architectures. [ABSTRACT FROM AUTHOR]

Introduction: A robotic wheelchair system enables people with disabilities and elderly people who are unable to operate traditional wheelchairs to move around. Advances in computer and software technologies have contributed to the provision of robotic wheelchairs and its tracking system to suit the needs of the healthcare sector. Developing a quality software system requirements specification and performing testing on the requirements are critical as the users involve patients who suffer musculoskeletal disorders. Methods: This research paper presents a robotic wheelchair and its software system requirements; a testing environment; and a requirements-based testing strategy to ensure the software system comply with the requirements including the functional and technological constraints of the wheelchair system. Results: The testing strategy was implemented to calculate Average Percentage of Faults Detected (APFD) and the result quantify 92.19% APFD rates of fault detection with 92.19%. This result delivers an effectively improving test coverage. Conclusion: The proposed testing environment and the requirements-based testing strategy enable requirements testing to be conducted from the very beginning of the software development life cycle. [ABSTRACT FROM AUTHOR]

Flocking is a social animals' common behaviour observed in nature. It has a great potential for real-world applications such as exploration in agri-robotics using low-cost robotic solutions. In this paper, an extended model of a self-organised flocking mechanism using heterogeneous swarm system is proposed. The proposed model for swarm robotic systems is a combination of a collective motion mechanism with obstacle avoidance functions, which ensures a collision-free flocking trajectory for the followers. An optimal control model for the leader is also developed to steer the swarm to a desired goal location. Compared to the conventional methods, by using the proposed model, the swarm network has less requirement for power and storage. The feasibility of the proposed self-organised flocking algorithm is validated by realistic robotic simulation software. [ABSTRACT FROM AUTHOR]

Model-driven engineering (MDE) addresses central aspects of robotics software development. MDE could enable domain experts to leverage the expressiveness of models, while implementation details on different hardware platforms would be handled by automatic code generation. Today, despite strong MDE efforts in the robotics research community, most evidence points to manual code development being the norm. A possible reason for MDE not being accepted by robot software developers could be the wide range of applications and target platforms, which make all-encompassing MDE IDEs hard to develop and maintain. Therefore, we chose to leverage a large corpus of open-source software widely adopted by the robotics community to extract common structures and gain insight on how and where MDE can support the developers to work more efficiently. We pursue modeling as a complement, rather than imposing MDE as separate solution. Our previous work introduced metamodels to describe components, their interactions, and their resulting composition. In this paper, we present two methods based on metamodels for automated generation of models from manually written artifacts: (1) through static code analysis and (2) by monitoring the execution of a running system. For both methods, we present tools that leverage the potentials of our contributions, with a special focus on their application at runtime to observe and diagnose a real system during its execution. A comprehensive example is provided as a walk-through for robotics software practitioners. [ABSTRACT FROM AUTHOR]

Background: Navigation and robotic-guided systems are being used more often to facilitate efficient and accurate placement of hardware during spinal surgeries. Preoperative surgical planning is a key step in the safe use of these tools. No studies have yet investigated the predictive accuracy of surgical planning using a robotic guidance system. Methods: Data were prospectively collected from patients in whom Mazor X-Align ™ [Medtronic Inc., Minneapolis, MN., USA] robotic guidance system software was used to plan their spinal instrumentation in order to achieve the best possible correction and the plans executed intraoperatively under robotic guidance. Results: A total of 33 patients (26 females, 7 males) were included. Their mean age was 51 years (12–79), and their mean BMI was 23.90 (15.55–35.91). Their primary diagnoses were scoliosis (20), kyphosis (5), spondylolisthesis (4), adjacent segment degeneration (3), and metastatic tumor (1). Preoperatively, the patients' mean coronal Cobb Angle (CA) was 36.5 ± 14.4°, and their mean sagittal CA was 27.7 ± 20.0°. The mean planned correction coronal CA was 0.2 ± 1.2°, and the mean planned correction sagittal CA was 28.4 ± 16.7°. Postoperatively, the patients' mean coronal CA that was achieved was 5.8 ± 7.4°, and their mean sagittal CA was 31.0 ± 18.3°. The mean difference between the planned and achieved angles was 5.5 ± 7.4° for the coronal, and 9.03 ± 9.01° for the sagittal CA. For the thoracic kyphosis and lumbar lordosis, the mean difference between the planned and postoperatively measured values was 15.3 ± 10.8 and 12.8 ± 9.6, respectively. Conclusion: This study indicates that the predictive accuracy of the use of preoperative planning software and robotic guidance to facilitate the surgical plan is within 6° and 9° in the coronal and sagittal planes, respectively. [ABSTRACT FROM AUTHOR]

Open-source Software (OSS) provide attractive solutions for complementing Mechatronics and Robotics Engineering (MRE) education due to their numerous advantages such as free access, customizability and wide community support, increased adoption and utilization in industry, etc. To provide a deeper insight on the current status, limitations, and potentials of the OSS, a summary of the results of an online survey, conducted among various community stakeholders, is included. Furthermore, the two parts of this contribution are intended to provide an exposure to the OSS which have the potential to be used in MRE education. To this end, two specific problems, namely, model simulation and analysis of a DC motor (Part I) and controller implementation for a 2-DOF robot manipulator (Part II), are solved using Python, Java, Modelica, GNU Octave, and Gazebo. The systems chosen for this work are some of the most-commonly encountered systems and the considered problems, i.e. model simulation, analysis, and control implementation, are fundamental problems in the context of MRE. Therefore, this work can help MRE instructors familiar with these OSS to easily integrate them into their respective courses. On the other hand, the students can also greatly benefit from this work as it provides an entry point into applying different OSS in MRErelated courses and projects. Exposure to various ways in which an MRE problem is translated into a software solution enables the students to generalize their problem-solving process across different computational tools. Students equipped with such a skillset would potentially have a flexible mindset and could make well-balanced and informed judgements when devising a solution to a real-world engineering problem. Full code scripts for each of the OSS introduced in this work, along with Matlab which is intended as a point of comparison, are included on the GitHub repository of the paper to provide free access to the community and to help with widespread adoption of the OSS in MRE higher education. [ABSTRACT FROM AUTHOR]