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
    Towards High-Payload Admittance Control for Manual Guidance with Environmental Contact
    ( 2022)
    Haninger, Kevin
    ;
    Radke, Marcel
    ;
    Vick, Axel
    ;
    Krüger, Jörg
    Force control enables hands-on teaching and physical collaboration, with the potential to improve ergonomics and flexibility of automation. Established methods for the design of compliance, impedance control, and collision response can achieve free-space stability and acceptable peak contact force on lightweight, lower payload robots. Scaling collaboration to higher payloads can allow new applications, but introduces challenges due to the more significant payload dynamics and the use of higher-payload industrial robots. To achieve high-payload manual guidance with contact, this paper proposes and validates new mechatronic design methods: standard admittance control is extended with damping feedback, compliant structures are integrated to the environment, and a contact response method which allows continuous admittance control is proposed. These methods are compared with respect to free-space stability, contact stability, and peak contact force. The resulting methods are then applied to realize two contact-rich tasks on a 16 kg payload (peg in hole and slot assembly) and free-space co-manipulation of a 50 kg payload.
  • 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.
  • Publication
    Intuitive robot programming through environment perception, augmented reality simulation and automated program verification
    ( 2018)
    Wassermann, Jonas
    ;
    Vick, Axel
    ;
    Krüger, Jörg
    The increasing complexity of products and machines as well as short production cycles with small lot sizes present great challenges to production industry. Both, the programming of industrial robots in online mode using hand-held control devices or in offline mode using text-based programming requires specific knowledge of robotics and manufacturer-dependent robot control systems. In particular for small and medium-sized enterprises the machine control software needs to be easy, intuitive and usable without time-consuming learning steps, even for employees with no in-depth knowledge of information technology. To simplify the programming of application programs for industrial robots, we extended a cloud-based, task-oriented robot control system with environment perception and plausibility check functions. For the environment perception a depth camera and pointcloud processing hardware were installed. We detect objects located in the robot's workspace by pointcloud processing with ROS and the PCL and add them to the augmented reality user interface of the robot control. The combination of process knowledge from task-oriented application programming and information about available workpieces from automated image processing enables a plausibility check and verification of the robot program before execution. After a robot program has been approved by the plausibility check, it is tested in an augmented reality simulation for collisions with the detected objects before deployment to the physical robot hardware. Experiments were carried out to evaluate the effectiveness of the developed extensions and confirmed their functionality.
  • Publication
    Distributed Motion Planning for Industrial Random Bin Picking
    ( 2018)
    Vonasek, Vojtech
    ;
    Vick, Axel
    ;
    Krüger, Jörg
    The task of bin picking is to automatically unload objects from a container using a robotic manipulator. A widely used solution is to organize the objects into a predictable pattern, e.g., a workpiece carrier, in order to simplify all integral subtasks like object recognition, motion planning and grasping. In such a case, motion planning can even be solved offline as it is ensured that the objects are always at the same positions. However, there is a growing demand for non-structured bin picking, where the objects can be placed randomly in the bins. This arises from recent trends of transforming classical factories into smart production facilities allowing small lot sizes at the efficiency of mass production. Due to unknown positions of the objects in the non-structured bin picking scenario, trajectories for the manipulator cannot be precomputed, but they have to be computed online. Sampling-based motion planning methods like Rapidly Exploring Random Tree (RRT) can be used to plan the trajectories. In this paper, we propose a modification of RRT for distributed motion planning aiming to reduce the runtime. The planning task is first simplified by computing several guiding waypoints. The waypoints are distributed to a set of planners running in parallel and each planner computes a short trajectory between two given waypoints. Connecting the waypoints is easier than solving the original task, therefore each planner runs fast. In comparison to other parallel motion planning techniques, the proposed approach does not require any communication among the computational nodes, which is more suitable for cloud-based computing. The proposed work has been verified both in simulation and on a prototype of a bin picking system.