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An implementation and evaluation of large-scale multi-user human–robot collaboration with head-mounted augmented reality

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Advanced engineering Informatics 2025年 67卷

作者： Xiliu Yang Felix Amtsberg Benjamin Kaiser Lior Skoury Tim Stark Simon Treml Nils Opgenorth Aimée Sousa Calepso Michael Sedlmair Thomas Wortmann Alexander Verl Achim Menges Institute for Computational Design and Construction (ICD) University of Stuttgart Germany Cluster of Excellence Integrative Computational Design and Construction for Architecture (IntCDC) University of Stuttgart Germany Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Germany Institute for Computational Design and Construction Chair of Computing in Architecture (ICD-CA) University of Stuttgart Germany Visualization Research Center (VISUS) University of Stuttgart Germany

Human–robot collaboration (HRC) offers promising potential for more flexible and sustainable production practices in architecture and construction. This requires HRC setups to scale up from light-payload collaborative robots to conform with the scale of building construction while considering the safety and teamwork culture for workers. This research proposes a system for large-scale multi-user HRC using head-mounted augmented reality (AR) devices. To achieve this, we contribute three methods that work in conjunction: (1) an AR system that enables multiple users to share tasks and work together with robots; (2) a dynamic human task allocation engine that reacts to the changing production teams and task types; and (3) a safety zone generation and allocation method to configure human collaboration in shared space with large-scale robots. The system is evaluated using a case study of prefabricated timber cassettes combining discrete event simulations, a user study and a fabrication process demonstrator with an industry partner.

关键词： Human–robot collaboration Augmented reality Robotic fabrication Timber prefabrication Co-design

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Towards an Automated Product-Production System Design - Combining Simulation-based engineering and Graph-based Design Languages

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Procedia manufacturing 2020年 52卷 258-265页

作者： Karl Kübler Dominik Schopper Oliver Riedel Stephan Rudolph Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstr. 36 70174 Stuttgart Germany Institute of Aircraft Design (IFB) University of Stuttgart Pfaffenwaldring 31 70569 Stuttgart Germany Fraunhofer Institute for Industrial Engineering IAO Nobelstraβe 12 70569 Stuttgart Germany

In this paper, the authors elaborate a combination of graph-based design and simulation-based engineering into a new concept called Executable Integrative Product-Production Model (EIPPM). Today, the first collaborative process in engineering for all mechatronic disciplines is the virtual commissioning phase. Therefore, Digital Twins (DT) are modeled and run in a simulation. The authors see a hitherto untapped potential for the earlier, integrated and iterative use of DTs in a simulation-based engineering for the development of production systems. Seamless generation of and exchange between Model-, Software- and Hardware-in-the-Loop simulations is necessary. Feedback from simulation results will go into the design decisions after each iteration. The presented approach combines knowledge of the domain "production systems technology" together with the knowledge of the corresponding "product" using a so called Graph-based Design Language (GBDL). Its central data model, which represents the entire life cycle, results of an automatic translation step in a compiler. Since the execution of the GBDL can be repeated as often as desired with modified boundary conditions (e.g. through feedback), a design of experiment is made possible, whereby also unconventional solutions are considered. The novel concept aims at the following advantages: Consistent linking of all mechatronic domains through a data model (graph) from the project start, automatic design cycles exploring multiple variants for optimized product-production system combinations, automatic generation of simulation models starting with the planning phase, feedback from simulation-based optimization back into the data model.

关键词： Simulation-based engineering Graph-based Design Languages Virtual Commissioning Digital Twins Product-Production Model

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Web-based Platform for Data Analysis and Monitoring

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Procedia CIRP 2019年 86卷 31-36页

作者： Colin Reiff Stefan Oechsle Florian Eger Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstrasse 36 70174 Stuttgart Germany

With the increasing number of sensors installed in production systems and the associated amount of recorded data, a high potential for optimizing manufacturing processes is offered. Based on the gathered information, data analyzing methods can be used to identify correlations and thus, optimize complex multi-stage production systems with the goal of zero-defect manufacturing. For this purpose, multiple statistical methods have to be applied, which is often a time-consuming task and currently requires trained and experienced specialists. Furthermore, the investigated data must be kept up to date for the early recognition of changes possibly leading to cost-intensive scrap and production downtimes. To address these issues, a web-based platform with an intuitive user interface was developed. The platform can access and process various data sources using modular methods. In addition, as part of continuous monitoring, the results of these analyzing steps can be dynamically calculated. The aim of the platform is to make complex analysis processes accessible to machine operators and thus to combine domain expertise and statistical knowledge. The paper describes the underlying architecture and the relevant interfaces of the platform.

关键词： Data Analysis Monitoring Process Optimization

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Reinforcement Learning Approach to Vibration Compensation for Dynamic Feed Drive Systems

Reinforcement Learning Approach to Vibration Compensation fo...

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Artificial Intelligence for Industries (AI4I)

作者： Ralf Gulde Marc Tuscher Akos Csiszar Oliver Riedel Alexander Verl Institute of Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (数字)9781728140872

ISBN: (纸本)9781728140889

Vibration compensation is important for many domains. For the machine tool industry it translates to higher machining precision and longer component lifetime. Current methods for vibration damping have their shortcomings (e.g. need for accurate dynamic models). In this paper we present a reinforcement learning based approach to vibration compensation applied to a machine tool axis. The work describes the problem formulation, the solution, the implementation and experiments using industrial machine tool hardware and control system.

关键词： Vibrations machine tools Learning (artificial intelligence) Hardware Optimization Feeds Entropy

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Beyond Model-Based Systems engineering towards Managing Complexity

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Procedia CIRP 2020年 91卷 325-329页

作者： Jonathan Masior Benjamin Schneider Mehmet Kürümlüoglu Oliver Riedel Fraunhofer Institute for Industrial Engineering IAO Nobelstrasse 12 Stuttgart 70569 Germany University of Stuttgart Institute for Human Factors and Technology Management IAT Nobelstrasse 12 Stuttgart 70569 Germany University of Stuttgart Institute for Control Engineering of Machine Tools and Manufacturing Units ISW Seidenstrasse 36 Stuttgart 70174 Germany

Systems engineering domain lacks in methodologies for integration of development artefacts (e.g. requirements, functions, geometrics, or behavior) and enterprise models (e.g. organizational structures, processes, or IT infrastructure). Especially the rising complexity driven by integrated product service systems, smart services, systems of systems and cyber physical systems (CPS) leads to a new paradigm further on called Advanced Systems engineering (ASE). It empowers enterprises to cope with such complex developments. The employment of ASE technologies in design and manufacturing enterprises requires a reachability of technical information and continuity along vertical and horizontal dimensions. A widely used approach to implement this is Model-based System engineering (MBSE). This paper introduces a solution to achieve the goals of manufacturing excellence as well as complexity management by identifying and analyzing relevant requirements and possible approaches for an innovative simulation enabling and executable modelling language, the so-called advanced MBSE+.

关键词： MBSE Model Based Systems engineering PLM Product Lifecycle Management IT Infrastructure Cyber Physical Systems Advanced Systems engineering

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Reinforcement Learning of a Robot Cell control Logic using a Software-in-the-Loop Simulation as Environment

Reinforcement Learning of a Robot Cell Control Logic using a...

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Artificial Intelligence for Industries (AI4I)

作者： Florian Jaensch Akos Csiszar Janik Sarbandi Alexander Verl Institute of Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (数字)9781728140872

ISBN: (纸本)9781728140889

This paper introduces a method for automatic robot programming of industrial robots using reinforcement learning on a Software-in-the-loop simulation. The focus of the the paper is on the higher levels of a hierarchical robot programming problem. While the lower levels the skills are stored as domain specific program code, the combination of the skills into a robot control program to solve a specific task is automated. The reinforcement learning learning approach allows the shopfloor workers and technicians just to define the end result of the manufacturing process through a reward function. The programming and process optimization is done within the learning procedure. The Software-in-the-loop simulation with the robot control software makes it possible to to interpret the real program code and generate the exact motion. The exact motion of the robot is needed in order to find not just an optimal but also a collision-free policy.

关键词： Optimization Learning (artificial intelligence) Service robots Robot control Software

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Real-time co-simulation for the virtual commissioning of production systems

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Procedia CIRP 2019年 79卷 397-402页

作者： Christian Scheifele Alexander Verl Oliver Riedel Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstr. 36 Stuttgart 70174 Germany

During virtual commissioning, the real control technology is put into operation in advance using a model-based digital twin of the production system. The growing demands on the significance of digital twins result in the need for higher model depths and model scopes of the behavior models used. However, new approaches to enhance the usable computing power in a real-time simulation are required. This paper presents a real-time co-simulation platform for virtual commissioning. The platform includes the integration of powerful technology-specific simulation solutions based on integration interfaces and a real-time co-simulation architecture based on partitioning, parallelization, synchronization and data exchange mechanisms.

关键词： real-time co-simulation hardware-in-the-loop simulation virtual commissioning digital twin virtual CNC physics-based simulation

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Test case generation for production systems with model-implemented fault injection consideration

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Procedia CIRP 2019年 79卷 268-273页

作者： Karl Kübler Elmar Schwarz Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstr. 36 70174 Stuttgart Germany

Complex production systems, which have to handle product diversity and short product life cycles, can only be stable and efficient when successfully tested prior to their start-up. Also, changes in automation software within the life cycle of a production system should be verified through repetitive testing before applying the new software version. Therefore, test automation in combination with fault injection on a virtual model of the production system is seen as the next step to improve the verification and validation of a production system. This work presents an approach to achieve negative test cases for a test automation framework.

关键词： Negative testing Test automation Virtual commissiong Hardware-in-the-loop

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Method for load-capable path planning in multi-axis fused deposition modeling

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Procedia CIRP 2019年 84卷 335-340页

作者： Frederik Wulle Martin Wolf Oliver Riedel Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstr. 36 70174 Stuttgart Germany

Additive manufacturing (AM) technologies have evolved from a niche application for rapid prototyping into a crucial technological and economically significant industry for functional parts. However, many processes cannot guarantee the required component properties for industrial applications. Here, anisotropic strength properties introduced in Fused Deposition Modeling (FDM) are major constraints. These production-related strength properties originate in the weak bonds between plastic beads and thus between layers, which considerably affects the strength of the part in multi-axial stress conditions. Multi-axis FDM printing enables the diminishment of this effect by using Curved Layer Slicing. However, suitable path planning tools have not been developed to realize this approach on an industrial level. This paper describes a method for strength optimization under consideration of the manufacturing boundary conditions. This path planning method is based on a subdivision of the CAD part into sub-volumes, which comprise homogeneous sets of principal stress trajectories, as determined by the Finite Element Analysis. Subsequently, the sub-volumes are sliced individually using a Curved Layer Slicing approach and paths on the different layers are aligned with the principal stress trajectories. This method generates and uses strength-oriented meta data, which closes a crucial interface between CAD, CAM and AM processes.

关键词： Additive manufacturing Design optimization machine tool Polymer

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Production planning and control systems – a new software architecture Connectivity in target

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Procedia CIRP 2019年 79卷 361-366页

作者： Carsten Ellwein Anja Elser Oliver Riedel Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 D-70174 Stuttgart Germany

Since the rise of production planning and control systems those systems were subject to changes and further development due to new requirements and possibilities. Recently, Industry 4.0 and especially the cloud manufacturing paradigm brought up new requirements as connectivity demands, which are not fulfilled by current realizations of production planning and control systems. To adapt such systems to connectivity requirements, current software architectures have to be revised. Therefore, within this paper a new software architecture for production planning and control systems is introduced providing a basis for data exchange in-between such systems.

关键词： Planning control systems Software architecture Industry 4.0 Cloud manufacturing

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