Construct redundancy in process modelling grammars: Improving the explanatory power of ontological analysis

Conceptual modelling supports developers and users of information systems in areas of documentation, analysis or system redesign. The ongoing interest in the modelling of business processes has led to a variety of different grammars, raising the question of the quality of these grammars for modelling. An established way of evaluating the quality of a modelling grammar is by means of an ontological analysis, which can determine the extent to which grammars contain construct deficit, overload, excess or redundancy. While several studies have shown the relevance of most of these criteria, predictions about construct redundancy have yielded inconsistent results in the past, with some studies suggesting that redundancy may even be beneficial for modelling in practice. In this paper we seek to contribute to clarifying the concept of construct redundancy by introducing a revision to the ontological analysis method. Based on the concept of inheritance we propose an approach that distinguishes between specialized and distinct construct redundancy. We demonstrate the potential explanatory power of the revised method by reviewing and clarifying previous results found in the literature

Smooth Spline-based Trajectory Planning for Semi-Rigid Multi-Robot Formations

This paper presents an approach for smooth trajectory planning in semi-rigid nonholonomic mobile robot formations using Bezier-splines. Unlike most existing approaches, the focus is on maintaining a semi-rigid formation, as required in many scenarios such as object transport, handling or assembly. We use a Relaxed A* planner to create an optimal collision-free global path and then smooth this path using splines. The smoothed global path serves to create target paths for every robot in the formation. From these paths, we then calculate the trajectories for each robot. In an iterative process, we match the velocities of the robots so that all trajectories are synchronized, and the dynamic limits of all robots are maintained. We provide experimental validation, which confirms no violation of the dynamic limits and shows an excellent control performance for a system of three robots moving at 0.3 m/s

Contour Tracking Control for Mobile Robots applicable to Large-scale Assembly and Additive Manufacturing in Construction

In the construction industry, as well as during the assembly of large-scale components, the required workspaces usually cannot be served by a stationary robot. Instead, mobile robots are used to increase the accessible space. Here, the problem arises that the accuracy of such systems is not sufficient to meet the tolerance requirements of the components to be produced. Furthermore, there is an additional difficulty in the trajectory planning process since the exact dimensions of the pre-manufactured parts are unknown. Hence, existing static planning methods cannot be exerted on every application. Recent approaches present dynamic planning algorithms based on specific component characteristics. For example, the latest methods follow the contour by a force-controlled motion or detect features with a camera. However, in several applications such as welding or additive manufacturing in construction, no contact force is generated that could be controlled. Vision-based approaches are generally restricted by varying materials and lighting conditions, often found in large-scale construction. For these reasons, we propose a more robust approach without measuring contact forces, which, for example, applies to large-scale additive manufacturing. We based our algorithm on a high-precision 2D line laser, capable of detecting different feature contours regardless of material or lightning. The laser is mounted to the robot's end-effector and provides a depth profile of the component's surface. From this depth data, we determine the target contour and control the manipulator to follow it. Simultaneously we vary the robot's speed to adjust the feed rate depending on the contour's shape, maintaining a constant material application rate. As a proof of concept, we apply the algorithm to the additive manufacturing of two-layer linear structures made from spray PU foam. When making these structures, each layer must be positioned precisely on the previous layer to obtain a straight wall and prevent elastic buckling or plastic collapse. Initial experiments show improved layer alignment within 10 % of the layer width, as well as better layer height consistency and process reliability

Handling of large and heavy objects using a single mobile manipulator in combination with a roller board

This paper presents a method for autonomous loading, transportation, and unloading of large objects using a nonholonomic mobile manipulator. Here, the size of the transported object is considerably larger than the size of the mobile platform, which is made possible through the use of a roller board. In this way, the mobile manipulator can handle objects that exceed the manipulator's payload. The robot can load and unload the object onto its platform using the differential kinematics of the system for a null space motion to maintain the object's position in space. In order to localise the object, we apply 3D-perception using a depth-camera. While transporting the object to its destination, the robot is considered a tractor-trailer-wheeled system and can navigate using SLAM. Kinematic modelling and practical evaluation prove that the system can potentially take over arduous transportation tasks

A Comparison of Different Approaches for Formation Control of Nonholonomic Mobile Robots regarding Object Transport

Controlling the formation of several mobile robots allows for the connection of these robots to a large virtual unit. This enables a group of mobile robots to carry out tasks that a single robot could not perform. For this purpose, the use of nonholonomic mobile robots is especially useful, as they often have a higher payload and are suitable for a wider range of terrains. However, most research in the area of formation control is focused on holonomic robots, since their superior mobility allows for better control and allows for the research on more sophisticated control techniques. The remaining articles explicitly dealing with nonholonomic robots often do cover common controllers, but do not include realistic simulations or comparison of different controls on the same trajectory. Therefore, in this paper, we present a comparative analysis of two frequently used control approaches. We compare the behavior of a l-?-controller and a Cartesian reference-based controller with different types of reference value generation and pose determination. The evaluation of all resulting control schemes is based on the task of collaborative object transport. To do so, we selected performance criteria geared towards applicability in real processes. In addition, we used an error model, which takes into account the noise and accuracy of all sensors (IMU and encoder) as well as the drift in odometry caused by the slip of the robot's wheels. The comparison includes a series of simulations using two trajectories with a changing number of robots and different formation geometries. In the simulations we got slightly better results for the Cartesian control law

A Method to Distinguish Potential Workplaces for Human-Robot Collaboration

The high dynamics of globalized markets and their increase in competition, as well as the demographic changes in western countries causing an increasing shortage of skilled personnel are resulting in major challenges for production companies today. These challenges relate in particular to the processes of assembly forming the last process step in the value chain due to its high share of manual labor. Collaborative assembly, which is characterized by immediate interaction of humans and robots, utilizes the strengths of both partners and is seen as an opportunity to achieve a higher level of flexibility in assembly just as well to support and relieve people of for instance non-ergonomic tasks through automation at work. Although almost every robot manufacturer already has collaborative systems in its product portfolio, these are not yet widely used in industrial production. This might have a variety of reasons, such as the fear of a risky investment or the lack of expertise within the company related to collaborative systems. This article shows a conceptual method that helps companies implementing human-robot-collaboration in their production more quickly and with less implied risk, thus addressing the forthcoming challenges. As a first step, companies must be qualified to make a suitable selection for a possible collaboration scenario. To achieve this, they need a tool to analyze and to evaluate their production processes according to their suitability for human-robot-collaboration. An important feature for an easy and effective use is that the process is formalized so that employees of companies can quickly and easily analyze different processes. The necessary criteria and procedures are developed accordingly and are integrated into the selection method. The main goal is to give the company a recommendation which of their processes are most suitable for human-robot-collaboration, so that they can be used effectively in their production

LiDAR-Based Localization for Formation Control of Multi-Robot Systems

Controlling the formation of several mobile robots allows for the connection of these robots to a larger virtual unit. This enables the group of mobile robots to carry out tasks that a single robot could not perform. In order to control all robots like a unit, a formation controller is required, the accuracy of which determines the performance of the group. As shown in various publications and our previous work, the accuracy and control performance of this controller depends heavily on the quality of the localization of the individual robots in the formation, which itself depends on the ability of the robots to locate themselves within a map. Other errors are caused by inaccuracies in the map. To avoid any errors related to the map or external sensors, we plan to calculate the relative positions and velocities directly from the LiDAR data. To do this, we designed an algorithm which uses the LiDAR data to detect the outline of individual robots. Based on this detection, we estimate the robots pose and combine this estimate with the odometry to improve the accuracy. Lastly, we perform a qualitative evaluation of the algorithm using a Faro laser tracker in a realistic indoor environment, showing benefits in localization accuracy for environments with a low density of landmarks

Efficient Use of Human-robot Collaboration in Packaging through Systematic Task Assignment

The ageing workforce in Germany is a major challenge for many companies in the assembly and packaging of high-quality products. Particularly when individual processes require an increased amount of force or precision, the employees can be overstressed over a long period, depending on their physical constitution. One way of supporting employees in these processes is human-robot collaboration, because stressful process steps can be automated in a targeted manner. With conventional automation, this is currently not economically possible for many processes, as human capabilities are required. In order to achieve a balanced cooperation based on partnership, as well as to use additional potentials and to consider restrictions such as process times, it is necessary to ensure a good division of tasks between human and machine. The methodical procedure of allocation presented in this paper is based on the recreation of the process from basic process modules conducted by the process planner. Subsequently, these processes are divided according to the respective capabilities and the underlying process requirements. The company-specific target parameters, such as an improvement in ergonomics, are taken into account. The assignment procedure is described in a practical use case in the packaging of high-quality electronic consumer goods. Furthermore, the use case demonstrates the applicability of the approach. For these purposes, the parameters and requirements of the initial and result state of the workplace are described. The procedure and the decisions of the approach are shown with regard to the achievable goals

Potential Biomarkers, Risk Factors and their Associations with IgE-mediated Food Allergy in Early Life: A Narrative Review

Food allergy affects the quality of life of millions of people worldwide and presents a significant psychological and financial burden for both national and international public health. In the past few decades, the prevalence of allergic disease has been on the rise worldwide. Identified risk factors for food allergy include family history, mode of delivery, variations in infant feeding practices, prior diagnosis of other atopic diseases such as eczema, and social economic status. Identifying reliable biomarkers which predict the risk of developing food allergy in early life would be valuable in both preventing morbidity and mortality and by making current interventions available at the earliest opportunity. There is also the potential to identify new therapeutic targets. This narrative review provides details on the genetic, epigenetic, dietary and microbiome influences upon the development of food allergy and synthesizes the currently available data indicating potential biomarkers. While there is a large body of research evidence available within each field of potential risk factors, there are very limited number of studies which span multiple methodological fields, for example including immunology, microbiome, genetic/epigenetic factors and dietary assessment. We recommend that further collaborative research with detailed cohort phenotyping is required to identify biomarkers, and whether these vary between at-risk populations and the wider population. The low incidence of oral food challenge confirmed food allergy in the general population, and the complexities of designing nutritional intervention studies will provide challenges for researchers to address in generating high quality, reliable and reproducible research findings.\nFood allergy affects the quality of life of millions of people worldwide and presents a significant psychological and financial burden for both national and international public health. Identifying reliable biomarkers which predict the risk of developing food allergy would be valuable in both preventing morbidity and mortality and by making current interventions available at the earliest opportunity. This review provides details on the genetic, epigenetic, dietary and microbiome influences upon the development of food allergy. This helps in identifying reliable biomarkers to predict the risk of developing food allergy, which could be valuable in both preventing morbidity and mortality and by making interventions available at the earliest opportunity.</p