Human-Robot Collaboration (HRC) offers potential for flexible manufacturing, especially in small and medium-sized enterprises, but existing systems often lack adaptability to dynamic environments and human needs. This paper presents a novel, skill-based framework for user-centric, Quality of Service (QoS) based orchestration of HRC workflows. Our three-layer architecture separates non-real-time orchestration and workflow management from real-time, safety-critical execution, coordinated via a user-friendly interface using our Gantt chart-based Robot Collaboration Language. The framework allows users to define QoS goals (e.g., speed, energy efficiency, ergonomics), influencing high-level orchestration and low-level motion planning. This paper details the implementation and demonstrates the framework’s structure. It contributes towards more flexible, efficient, and human-aware robotic systems by providing an integrated approach to adaptive HRC workflow execution.

Domain-specific languages (DSLs) can simplify the programming of human-robot collaboration (HRC) systems for non-experts. However, executing skill-based DSLs for HRC programming requires integrating various production resources such as robots, humans, and sensors. Therefore, domain overlapping requirements must be considered when choosing an appropriate execution approach. This paper identifies and explains key requirements such as flexible interfaces, dynamic capability discovery, task dependency resolution, spatial awareness, continuous monitoring, and user interfaces. Through a comprehensive literature review and gap analysis, we identify trade-offs in execution methodologies. Based on this, we propose an orchestration-based strategy that offers centralized coordination, extendable interface integration, and monitoring capabilities to address current limitations in executing DSLs in HRC applications.

The evolution from Industry 3.0 to 5.0 has marked significant advancements in human-robot collaboration (HRC), with the latest stage emphasizing a human-centric approach that integrates robots as collaborative partners. Despite the potential of HRC, challenges such as communication barriers, safety concerns, and the complexity of dynamic interactions persist, potentially hindering optimal collaboration. To address these challenges, this research introduces a modeling approach that incorporates a detailed kinematic description of human movements within the workflow. By mapping human movements and calculating robot paths proactively, the proposed method aims to enhance interaction safety and efficiency, transitioning from reactive to proactive path planning.

The collaboration between humans and robots offers opportunities that are not achievable separately. However, a strategy for collaboration is required, as they differ in their behavior and perception. This work-in-progress paper outlines future research activities in this field, focusing on the integration of collision avoidance into robot movements. Therefore, trajectory planning is formulated as an optimization problem, which considers the human being but also finds the optimal trajectory according to a certain criterion. This reduces the cycle time or the energy required to drive the robot. The description as a multibody system enables a digital twin allowing planning in advance, but also the possibility of real-time control. This creates the basis for trust in the collaboration.

Industry 4.0 envisions Cyber-Physical Production Systems (CPPSs) to foster adaptive production of mass-customizable products. Manufacturing approaches based on capabilities and skills aim to support this adaptability by encapsulating machine functions and decoupling them from specific production processes. At the 2022 IEEE conference on Emerging Technologies and Factory Automation (ETFA), a special session on capability- and skill-based manufacturing is hosted for the fourth time. However, an overview on capability- and skill based systems in factory automation and manufacturing systems is missing. This paper aims to provide such an overview and give insights to this particular field of research. We conducted a concise literature survey of papers covering the topics of capabilities and skills in manufacturing from the last ten years of the ETFA conference. We found 247 papers with a notion on capabilities and skills and identified and analyzed 34 relevant papers which met this survey’s inclusion criteria. In this paper, we provide (i) an overview of the research field, (ii) an analysis of the characteristics of capabilities and skills, and (iii) a discussion on gaps and opportunities.

In this paper, we present a user-selectable control unit to make complex robot systems easier to operate. Search and rescue robots are primarily used for obtaining information and manipulating dangerous objects or supporting emergency forces in dealing with crisis situations. Based on hazardous mission scenarios in which mobile robot systems are confronted with complex manipulation and manoeuvring tasks (e.g., leakage of contaminants), new methods and concepts in the area of robot decision making, sensor data presentation and control concepts were developed to facilitate the handling and operation of assistance robots. The flexibility of the control concept approach is intended to increase the confidence of the emergency services and to provide intuitive operation of the assistance robots for every user. An intuitive control and stable communication for both control commands and feedback from the robot itself increase trust in the robotic system and its acceptance by the operators. These developments have been investigated in field trials with different types of robots and with network communication constraints.

The extensive automation in production plants usually requires complex control logic for interconnection intralogistics systems. The required flexibility in modern production processes makes it necessary to apply frequent changes to the PLC programs of the transport system. This and the rapidly growing number of different hardware manufacturers make it difficult to design a uniform material flow concept. The problem requires new means to make transport systems versatile in a flexible production plant. In particular, the universal communication between the different parts of the system as well as the visualization and possibility of autonomous simulation are topics to be addressed. In this paper, a new framework is proposed to configure the components of a generic transport system and generating OPC UA based control logic and a corresponding simulation model (i.e Digital Twin).

In many industrial environments physical process values are still measured using analog gauges. An automatic reading of these instruments using wireless or wired data connections is often not feasible, due to cost- or technical issues. In such cases manual reading using human personnel is currently state-of-the-art. Especially in large plants (e.g. oil & gas refinery) these tasks are very error-prone, time-consuming and often dangerous due to exposed positions of the gauges. Recent research in the domain of autonomous robots and machine vision broadened the way of implementing either assistive or fully autonomous systems for reading analog gauges in hazardous environments. Therefore this work introduces a novel method for the detection of the gauge itself, the detection of the pointer needle and the extraction of information from the markings on the gauge. This allows the extraction of a physical measurement value without any prior knowledge about the gauge.

Current trends in the context of Industry 4.0 attempt to minimize production costs and increase productivity. Nowadays control systems consist of components from various manufacturers. Therefore, it must be possible to easily connect these components without any platform specific interface definitions or software implementations. A first approach is the industry standard OPC UA, which enables the definition of hardware-independent interfaces of automation components (i.e. PLCs). Many manufacturers already start to integrate this standard into their products but unfortunately it only defines the transport layer of data and not which data is to be transported. Therefore, vendor-overlapping communication is only possible in case there is common understanding of how variables and functions are named and interpreted. A promising step towards this is to define skills as atomic unit for modeling and operating automation processes. Consequently the fixed mapping of skills and manufacturing stations is no more necessary during the engineering process. When applying skill-based engineering concepts it is only important to model and orchestrate skills that can accomplish the required tasks. The mapping between required and available skills can be done on the fly. Accordingly in this paper we propose an OPC UA-based multi-layered approach to orchestrate and execute manufacturing workflows using production task-based skills operated on flexibly linked and different hardware components (i.e. manufacturing stations).

Upcoming trends in manufacturing focus on flexible configuration of products up to lot-size one. This mass customization raises a need of flexible manufacturing and production systems that should react on fast changing market demands. As a result, it is getting more and more important to model all needed assets or skills in an user-oriented and configurable manner. Assets can represent any type of data or skill information needed in a manufacturing domain. Data information could be for example shown to a human worker (e.g. work instructions, images, videos or animations) or could be required by robots (e.g. coordinates, velocities). Skill information represent any type of executable functionality provided by a device. This paper shows a generic approach to model needed context information of (collaborative) manufacturing tasks. This approach supports skill-based engineering enabling the usage of various components from different vendors. In addition, this work presents a domain-specific modeling approach of skills including the definition and validation of custom modeling rules.

Modeling assembly and manufacturing tasks accomplished by machines (i.e., robots) using offline programming is quite common today. Considering lot-size-one products human work is still necessary, whereas human tasks are often not considered during the modeling and offline programming process. Therefore this work presents a generic approach, which provides the ability to model variable work tasks of humans and machines together including the variability of any process data using a runtime-decision model. Depending on the detail level of the model it is possible to generate various assets such as work instructions, machine programs or human-machine interfaces. The ADAPT (Asset-Decision-Action-Property-RelaTionship) modeling approach is initially illustrated using a common LEGO assembly use case. Additionally we present a first implementation of a BPMN-based workflow designer that enables the user to model assembly and manufacturing processes in an intuitive way.

The increasing number of variants results in decreasing lot sizes in the assembly and manufacturing domain. Considering traditional approaches of automation using industrial robots, it is very time-consuming to permanently adapt industrial robots for specific product variants in assembly lines. One possible approach of resolving this issue is the use of human-robot-collaboration for specific assembly steps. However, this also means that, in addition to the robot program, a work instruction must be created for the human worker. With current methods no workflow can be modeled which is universally applicable for a human or a robot. Therefore, this paper presents a new approach, called Human Robot Time and Motion (HRTM). The method provides generic basic elements which can be performed by a human worker or a robot. Additionally, collaborative elements allow to model synchronous tasks and a communication between human/human, human/robot or robot/robot. The HRTM approach is initially demonstrated by modeling a simple workflow which can be performed by a human worker or a robot. Finally, we model a collaborative workflow using LegoⓇ DuploⓇ bricks and perform it at a workplace with a collaborative robot.

Over the past decade, a clear trend toward distributed automation in industrial systems was observable. This means that applications are executed at heterogeneous control devices and communication networks. One of the main drivers of this development was the availability of cheap computing and communication resources. Moreover, a strong market demand for operation and adaptation of automation and control services with no downtime is also often requested. As a result, appropriate approaches recovering and (re)configuring automation and control devices as well as even their services and functions during full operation are needed. The relatively new standard IEC 61499 “Function Blocks” provides a reference model for the development and implementation of distributed industrial process measurement and control systems (IPMCSs). It provides a scalable and open architecture to model distributed automation and control applications. The high-level goals of IEC 61499 can be summarized as interoperability, (re)configurability, and portability of distributed applications for IPMCS. Therefore, it provides a very good basis for dynamic (re)configuration and recovery of applications and status information in heterogeneous IPMCS and may master some of the shortcomings of present-day systems. The main purpose of this paper is to present and discuss a general concept for autonomous recovery of applications within the context of distributed automation and control systems which has been implemented using the IEC 61499 reference model.

Today's automation systems are increasingly composed of heterogeneous distributed components. The components of such systems communicate via different protocols and need to provide a pre-specified quality of service (QoS). For modeling such distributed applications new concepts like the standard IEC 61499 are available. But IEC 61499 does not sufficiently cover the description of the communication properties between subcomponents. However the architecture analysis and design language (AADL) seems to allow sufficiently formal modelling of communication parameters and QoS parameters. This paper compares the application modelling with IEC 61499 and AADL on the basis of a simple example and shows an approach how to map IEC 61499 applications to AADL. Both contribute to derivation of communication links between reliable distributed real time components automatically out of a system independent application description, a system description and mapping parameters.

Developers maintaining distributed control systems are facing significant problems when dealing with changing customer requirements during the development and operation of industrial production facilities. Research has so far largely focused on implementation-level engineering challenges. Model-driven approaches are seen as promising for dealing with the increasing complexity of adapting distributed control systems. We present an approach for capturing architectural variability of distributed IEC 61499 automation and control systems based on product line variability models. Our automated approach supports decision-driven derivation and adaptation of systems at runtime.