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First International Conference on Transdisciplinary AI (TransAI)

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

Reinforcement Learning (RL) has gained popularity for developing intelligent robots, but challenges such as sample inefficiency and lack of generalization persist. The choice of observation space significantly influences RL algorithms' sample efficiency in robotics. While end-to-end learning has been emphasized, it increases complexity and inefficiency as the agent must re-learn forward and inverse kinematics. To address these issues, we propose a straightforward approach that utilizes readily available control techniques, such as forward and inverse kinematics, to capitalize on domain knowledge. Our approach involves enhancing the observation space with task-space features and utilizing task-space inverse kinematics. Our contributions include a proposal for mathematical formulation and a framework for RL algorithms in robotics.

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Topology Matching of Branched Deformable Linear Objects

Topology Matching of Branched Deformable Linear Objects

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Manuel Zürn Markus Wnuk Armin Lechler Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

This paper presents a new method for correspondence estimation between a previously known topology of a branched deformable linear object and an image representation from a 3D stereo camera. Although frequently encountered in production, robotic deformable linear object manipulation still lacks reliable sensor feedback. Especially for branched deformable linear objects, such as wire harnesses, correspondence estimation is very challenging. Due to their flexible nature, they have an infinite-dimensional configuration space, such that visual appearances of the same object can vary strongly. Knowing the correspondence is vital for various applications, e.g., estimating valid grasping positions for robotic wire routing or augmented reality support for workers. Therefore, this paper presents a method for matching the topology of a branched deformable linear object to camera sensor data. Asymmetries in the wire harness design reduce the solution space by comparing the known topology of a model to the topology extracted from sensor data. The problem of finding the most likely solution to the matching problem requires features extracted from camera images. These features are used to construct a graph-based topology representation, which can then be matched to a graph-based topology representation of the known branched deformable linear object. The presented method is evaluated using multiple different non-overlapping configurations of a wire harness, showing the effectiveness of a graph-based segment matching approach.

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Co-Design of Structural Timber Components Through Automated Model Generation for manufacturing Simulation of Reconfigurable manufacturing Systems

Co-Design of Structural Timber Components Through Automated ...

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International Conference on Mechatronics and machine Vision in Practice (M2VIP)

作者： Benjamin Kaiser Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

manufacturing of products with high variability and small batch sizes, such as prefabricated timber building components, presents significant manufacturing challenges. In urban areas, the construction industry's relatively low productivity, coupled with rising demand for affordable housing and irregularly shaped spaces, calls for novel and innovative construction technologies. The method of computational design shows promise as a solution, allowing unique, optimized structures composed of individual components, departing from conventional modular construction. Automated prefabrication of these building components enhances construction productivity. Reconfigurable manufacturing systems offer a practical solution for addressing building component variations and changing project requirements, requiring frequent system re-configuration. The co-design process concurrently optimizes building components and manufacturing systems to ensure manufacturability and structural optimization through iterative design, validated by simulation. However, manual simulation implementation and validation for component manufacturability is time-consuming and error-prone, especially considering the numerous iterations and layout variants involved in the co-design process. This paper proposes a method for automatically generating and conducting simulations to check the manufacturability of building elements to enable co-design. The proposed method uses AutomationML as a modeling language for describing the manufacturing system and building components. We conduct several simulations with parametrically generated timber shell elements to validate the proposed method.

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Self-adaptive digital twin reference architecture to improve process quality

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Procedia CIRP 2023年 119卷 867-872页

作者： Ann-Kathrin Splettstößer Carsten Ellwein Andreas Wortmann Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 D-70174 Stuttgart Germany

The aim of software-defined manufacturing is a more adaptable production through software. This requires highly adaptive, versatile cyber-physical production systems (CPPSs), which react flexibly to changes and perform crucial adjustments. Self-adaptive digital twins (DTs) enable adaptability through monitoring the behavior of a CPPS, identifying problems, and determining adjustments for the optimization of processes. DTs work with an idealized representation of the CPPS. Changes in system behavior that negatively impact the process execution, e.g., caused by tool wear or variations of environmental influences, and, thus, the quality of the resulting product, are ignored. This ignorance leads to defective products, sub-optimal product quality, and hazardous CPPS states. To mitigate this, we present an approach to incorporate quality awareness into a model-driven reference architecture of a self-adaptive DT. The devised concept automatically analyzes and optimizes system behavior. To this end, a component for quality evaluation extends the reference architecture. The DT and CPPS are connected via OPC UA. To validate the approach, a fiber laser machine is utilized. The DT can operate both on a physical and a virtual laser machine.

关键词： Digital Twin Model-Driven Development Software-Defined manufacturing Quality Awareness

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Deep Learning-Based Instance Segmentation for Feature Extraction of Branched Deformable Linear Objects for Robotic Manipulation 19

Deep Learning-Based Instance Segmentation for Feature Extrac...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Zürn, Manuel Kienzlen, Annika Klingel, Lars Lechler, Armin Verl, Alexander Ren, Shiyi Xu, Weiliang Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 Stuttgart70174 Germany The University of Auckland Department of Mechanical and Mechatronics Engineering 20 Symonds St. Auckland1001 New Zealand

ISBN: (纸本)9798350320695

Branched deformable linear objects, like wire harnesses, are vastly used in the electrical industry to interconnect multiple electronic components while allowing small relative motions. Their deformable nature gives them an infinite-dimensional configuration space, which is challenging for robotic manipulation and requires sensor feedback about the actual configuration. Cameras have been used before in automation attempts as sensor feedback of branched deformable linear objects. However, image processing is sensible to occlusions and unstructured environments. This paper presents a method of using deep learning-based instance segmentation networks to extract topological features like connectors, clips, branch points and overlapping points on the branched deformable linear object. The topological features originate from features that can be used for matching a stretched representation of the branched deformable linear object to its sensor representation. Our results show that the network is capable of extracting the features for different datasets with high accuracy. Furthermore, this paper evaluates the use of preliminary results in the training process to facilitate annotation by predicting the labels. For now, this paper only uses 2D images of the branched deformable linear objects. Future work will also use depth images, such that individual deformable linear object features, such as length or radius, can be extracted from the images. We anticipate the usage of wire harness automation with robotic manipulation, augmented reality support of the worker or quality control of wire harnesses. © 2023 IEEE.

关键词： Feature extraction

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Navigating the Low-Code Landscape: A Comparison of Development Platforms

Navigating the Low-Code Landscape: A Comparison of Developme...

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Conference on Model Driven engineering Languages and Systems Companion (MODELS-C)

作者： Jörg Christian Kirchhof Nico Jansen Bernhard Rumpe Andreas Wortmann Software Engineering RWTH Aachen University acronio GmbH Aachen Germany Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Stuttgart Germany

Low-code development is a software-development paradigm that can reduce the conceptual gap between application domain problem expertise and software engineering solution expertise. Hence, it might be a vital means to reduce the impact of the world-wide scarcity of software-developers. Consequently, many different low-code development platforms (LCDPs) have surfaced in the last 5–10 years, which domain experts must understand to chose the best-possible LCDP for their applications. This choice is not made restricting to front-end features of these LCDPs, but also to back-end features, which the domain experts are usually less familiar with. To support domain experts in making this decision, we have investigated popular LCDPs for features relevant to domain experts. Our findings aim to guide these domain experts, but also researchers in better understanding the landscape of LCDPs.

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Recurrent Neural Network for Modelling a Contractive Soft Actuator 56

Recurrent Neural Network for Modelling a Contractive Soft Ac...

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56th International Symposium on Robotics, ISR Europe 2023

作者： Kienzlen, Annika Zürn, Manuel Kazemi, Shahab Xu, Weiliang Cheng, Leo K. Strommel, Martin Verl, Alexander Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Germany Department of Mechanical & Mechatronics Engineering University of Auckland New Zealand Auckland Bioengineering Institute University of Auckland New Zealand Department of Electrical & Electronic Engineering University of Auckland New Zealand

ISBN: (纸本)9783800761418

Robotic stomach simulators are designed and employed to model stomach motility and gain insights into the digestive process. These simulators consist of multiple nonlinear soft actuators. Their modelling enhances the controllability and optimisation possibilities and shows their geometry variations and deformations. By leveraging a dynamic model, it becomes possible to design time-efficient model-based controllers that handle the nonlinearities of the soft robot. However, the modelling of soft actuators is challenging due to their infinite number of degrees of freedom. In this paper, we propose a novel approach that maps the dynamics of a contractive soft actuator to a neural network. The short calculation time of neural networks combined with their ability to model complex relationships make them a promising approach for controlling soft actuators. Since the contractive behaviour of the soft actuator is difficult to capture, training data can be generated using a physical simulation model. The results demonstrate that a simple recurrent neural network can model similar dynamics to a physical simulation model with significantly reduced calculation times. Since a fast and precise computer model is necessary to capture the complex dynamics of the soft actuators accurately for control purposes, the recurrent neural network is promising. © VDE VERLAG GMBH Berlin Offenbach.

关键词： contractive actuation deep learning recurrent neural network soft robotics

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Ambiguity tolerant commissioning ontology: Targeting client communication

Ambiguity tolerant commissioning ontology: Targeting client ...

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2021 IEEE International Conference on engineering, Technology and Innovation, ICE/ITMC 2021

作者： Ellwein, Carsten Krimstein, Viktor Riedel, Oliver Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (纸本)9781665449632

There are various standards for the description of geometrical data, in terms of computer-aided design, as well as for the description of manufacturing processes. However, there is a lack in a data model that allows a product to be described partly by its geometry and partly by the description of the manufacturing process;whereby both forms of description are to be regarded as equivalent. Such a model would greatly facilitate communication in contract and job order manufacturing, especially in the computer-aided outsourcing of orders according to the cloud manufacturing paradigm. In this paper, this kind of data model is further justified and one ontological description, in compliance with existing standards, is introduced. © 2021 IEEE.

关键词： Ontology

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Survey on Robotic Systems Integration

Survey on Robotic Systems Integration

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Workshop on Robotics Software engineering (RoSE)

作者： Nadia Hammoudeh Garcia Andreas Wortmann Robot and Assistive Systems Department Fraunhofer Institute for Manufacturing Engineering and Automation (IPA) 70569 Stuttgart Germany Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart 70174 Stuttgart Germany

Software integration is central to successfully developing, deploying, and operating robotics applications. Yet, the particular integration process and its challenges are poorly understood. The continuous evolution of the robotics sector, incorporating constantly a growing number of technologies, makes the unification of processes increasingly complicated. Nevertheless, current research on robotics software integration largely focuses on specific integration activities instead of considering the overall activity as a process. To provide some insight into the state of robotics software integration, we drove a survey among researchers and practitioners in the field. In this survey, we inquired how robotics software integration is currently performed in order to identify similarities with traditional software development methodologies. Through this study, we discovered commonalities in the phases of the process and potential directions of a future research to address the current challenges in the area.

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Robot machining of thin-walled workpieces with automatically reconfigurable fixturing through feature analysis

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Procedia CIRP 2023年 120卷 1065-1070页

作者： Andreas Schütz Armin Lechler Alexander Verl Jürgen Fleischer Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstrasse 36 70174 Stuttgart Germany Institute of Production Science (wbk) Karlsruhe Institute of Technology Gotthard-Franz-Straße 5 76131 Karlsruhe Gremany

Machining of large scale thin-walled workpieces pose high requirements for fixturing because of large stiffness changes due to material removal. Automatically reconfigurable fixtures that allow in-process reconfiguration are a promising approach. In this paper, an efficient approach based on feature analysis is proposed for fixture reconfiguration planning. For this, material removal is simulated. At discrete points in time, feature analysis is performed and an approximated local stiffness map is calculated with weight functions derived from the features’ parameterizations. Viable fixture configurations are then identified through root finding and validated through simulation in Ansys and experimentally with a fixture jig. In both validations, workpiece deformation for drilling operations could be reduced to an acceptable level enabling the implementation's future use in industrial application.

关键词： industrial robot robot machining fixture reconfigurable filexible

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