Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Redundancy Concepts for Real-Time Cloud- and Edge-based Control of Autonomous Mobile Robots
    ( 2022)
    Nouruzi-Pur, Jan
    ;
    Lambrecht, Jens
    ;
    Nguyen, The Duy
    ;
    Vick, Axel
    ;
    Krüger, Jörg
    Deploying navigation algorithms on an edge or cloud server according to the Software-as-a-Service paradigm has many advantages for autonomous mobile robots in indus-trial environments, e.g. cooperative planning and less onboard energy consumption. However, outsourcing corresponding real-time critical control functions requires a high level of reliability, which cannot be guaranteed either by modern wireless networks nor by the outsourced computing infrastructure. This work introduces redundancy concepts, which enable real-time capability within these uncertain infrastructures by providing redundant computation nodes, as well as robot-controlled switching between them. Redundancies can vary regarding their physical location, robot behavior during the switchover process and degree of activeness while quality of service concerning the primary controller is sufficient. In the case that fallback redun-dancies are not continuously active, when a disturbance occurs an initial state estimation of the robot pose has to be provided and an activation time has to be anticipated. To gain some insights on expected behavior, redundant computation nodes are deployed locally on the robot and on an outsourced computation node and consequently evaluated empirically. Quantitative and qualitative results in simulation and a real environment show that redun-dancies help to significantly improve the robot-trajectory within an unreliable network. Moreover, resource-saving redundancies, which are not continuously active, can robustly take over control by using an estimated state.
  • Publication
    Networked Visual Servoing as Use-Case for Cloud-based Industrial Robot Control
    ( 2020)
    Vick, Axel
    ;
    Krause, Christian
    ;
    Krüger, Jörg
    Nowadays production industry and smart factory is dealing with methods of optimal resource load balancing and new types of flexible service-oriented strategies. It is seen crucial to adapt quickly to changes in manufacturing processes and new products or even integrate new hardware faster than the competition. Flexibility and Scalability can be improved by exchanging only a certain part of hardware and software without the need of touching all the other components. In this paper we present a methodical approach towards a typical use case in modern industrial robotic systems. The system consists of hardware components from different manufacturers which can be controlled and monitored separately by remote services. Those services can be combined to complex applications and integrate value added services. We show the independence and capability of exchangeable added value services running either centralized, decentralized, locally or remote. The experiments demonstrate how a process is improve by simply adding another service according to the Plug-and-Play paradigm. The service ensures the conditions of a computer vision system component to keep the reliability of the overall system workflow. In addition it will be demonstrated how system components could be virtualized in container-based cloud environments to save required on-board resources of the robotic system while keeping the whole system communication secure. Finally, results will be presented for different intercommunication scenarios.
  • Publication
    Visualizing trajectories for industrial robots from sampling-based path planning on mobile devices
    ( 2018)
    Guhl, Jan
    ;
    Vick, Axel
    ;
    Vonasek, Vojtech
    ;
    Krüger, Jörg
    Production lines are nowadays transforming into flexible modular and interconnected cells to react to rapidly changing product demands. The arrangement of the workspace inside the modular cells will vary according to the actual product being developed. Tasks like motion planning will not be possible to precompute. Instead, it has to be solved on demand. Planning the trajectories for the industrial robots with respect to changing obstacles and other varying environment parameters is hard to solve with classical path planning approaches. A possible solution is to employ sampling-based planning techniques. In this paper we present a distributed sampling-based path planner and an augmented reality visualization approach for verification of trajectories. Combining the technologies ensures a confirmed continuation of the production process under new conditions. Using parallel and distributed path planning speeds up the planning phase significantly and comparing different mobile devices for augmented reality representation of planned trajectories reveals a clear advantage for hands-free HoloLens. The results are demonstrated in several experiments in laboratory scale.
  • Publication
    Cloud-based active disturbance rejection control for industrial robots
    ( 2018)
    Briese, Clemens
    ;
    Vick, Axel
    ;
    Krüger, Jörg
    The classical design of industrial robot controllers relies strongly on constant and stable cycle times for any closed loop operation. Meanwhile, decentralizing robot control into independent services and rolling them out to virtual machines and cloud instances is an upcoming trend. The advantage of the distributed robot control lies in achieving full flexibility of location independent service execution. In contrast, the internet connectivity leads to unknown latency conditions and resulting unpredictable cycle times. That is not well handled by standard feedback controllers like PID or P-PI cascades. In addition to the time-critical aspect, the performance of a closed-loop control relies on the accuracy of the underlying model. Modeling is often labor-intensive and time-consuming. This paper presents four different implementations of a non-model based modified Switching Active Disturbance Rejection Control (ADRC) in a robotic use case. The comparison of these four concepts reveals the strengths and weaknesses of the ADRC approach regarding controller performance under the assumption of full dynamics compensation with tough communication conditions. By extending the Switching-ADRC approach by a gain-scheduler to smooth the switching between the linear and non-linear ADRC description and a static adjustment of control-parameters related to the measured round-trip time, the presented control-concept is able to stabilize the high-dynamic, partly unstable robot-system without model-information. The stability of the modified Switching-ADRC is demonstrated empirically by extensive experiments with a distributed industrial robot joint position control.
  • Publication
    Using OPC UA for Distributed Industrial Robot Control
    ( 2018)
    Vick, Axel
    ;
    Krüger, Jörg
    The production industry is confronted with a big change from classical factory planning to digitized and networked structures. The line-based or batch mass production of one and the same product over tens of years is developing to an end-user driven individualization with production cycles of less than one year. To react to the fast changing requirements on products and production infrastructure, machine tools and industrial robots as well as the complete intra-factory logistics, have to evolve to universal production tools with high connectivity, the cyber-physical production systems (CPPS). Current monolithic robot control architectures lack flexibility and scalability to support that short production cycles. This paper presents a distributed control architecture that is capable of reorganizing the production process on the fly. The control system uses OPC UA as communication layer and is capable of combining hardware control services together with high level control services and build individual software systems for each automation task. The system is highly scalable in terms of additional components, improved algorithms or location change. Experiments are implemented with an industrial robot with cameras and gripper in a human-robot collaborative pick and place use case.