Considering interdependencies for a dynamic generation of process chains for Production as a Service

Hermann, Jesko; David, Alexander; Wagner, Achim; Ruskowski, Martin

doi:10.1016/j.promfg.2020.10.202

Cited by 11 publications

(6 citation statements)

References 11 publications

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“…We consider a robotic manipulator with N joints. The dynamical model of a manipulator can be derived by Lagrange's equations of the second kind and formulated in a matrix form as M(q(t)) q(t) + C(q(t), q(t)) q(t) + g(q(t)) = τ (t), (1) where q(t) ∈ R N denotes the vector of generalized coordinates, which is the joint angular position vector. The inertia matrix is denoted by M(q(t)) ∈ R N ×N , C(q(t), q(t)) ∈ R N ×N maps the angular velocities q(t) to Coriolis and centrifugal torques, g(q(t)) ∈ R N is the vector of gravitational and τ ∈ R N denotes the vector of generalized torques.…”

Section: Dynamical Modelmentioning

confidence: 99%

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Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators

et al. 2022

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A flexible operation of multiple robotic manipulators operating in a dynamic environment requires online trajectory planning to ensure collision-free trajectories. In this work, we propose a real-time capable motion control algorithm, based on nonlinear model predictive control, which accounts for static and dynamic obstacles. The proposed algorithm is realized in a distributed scheme, where each robot optimizes its own trajectory with respect to the related objective and constraints. We propose a novel approach for collision avoidance between multiple robotic manipulators, where each robot accounts for the predicted movement of the neighboring robots. Additionally, we propose a method to reliably detect and resolve deadlocks occurring in a setup of multiple robotic manipulators. We validate our approach on pick and place scenarios involving multiple robotic manipulators operating in a common workspace in a realistic simulation environment set up in Gazebo. The robots are controlled using the Robot Operating System. Our approach scales up to 4 manipulators and computes a path for each robot in a simultaneous pick and place operation in 94% of all investigated cases without deadlock detection and 100 % of cases with the proposed deadlock resolution algorithm. In contrast, the investigated conventional path planners, such as PRM, PRM*, CHOMP and RRT-Connect, successfully plan a trajectory in at most 54% of all investigated cases for a simultaneous operation of 4 robotic manipulators hindering their application in setups of multiple manipulators.INDEX TERMS Robotic manipulators, collision avoidance, distributed model predictive control, motion control, deadlock, ROS.

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Section: Dynamical Modelmentioning

confidence: 99%

“…Modern industrial processes are increasingly dominated by shorter innovation and product life cycles, reflecting a growing demand for customized products [1]. Consequently, factory systems must become more flexible and adaptable [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators

et al. 2022

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“…We consider a robotic manipulator with N joints and neglect viscous and static friction. The dynamic model of the manipulator can be derived by means of the Lagrangian formalism and written in a matrix form as M(q(t))q(t) + C(q(t), q(t)) q(t) + g(q(t)) = τ (t), (1) where q(t) ∈ R N denotes the vector of generalized coordinates, which is the joint angular position vector. Furthermore, M(q(t)) ∈ R N ×N represents the inertia matrix, C(q(t), q(t)) ∈ R N ×N maps the angular velocities q(t) to Coriolis and centrifugal torques, g(q(t)) ∈ R N is the vector of gravitational and τ ∈ R N denotes the vector of generalized torques.…”

Section: Dynamic Modelmentioning

confidence: 99%

“…The new input u(t) ∈ R N compensates the non-linearity of the system dynamics given in (1). The non-linear control law in (2), referred to as inverse dynamics control or computed torque, leads to N double integrators for a closed loop system.…”

Section: Model Predictive Controllermentioning

confidence: 99%

Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game

Gafur¹,

Kanagalingam²,

Ruskowski³

2021

Preprint

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A flexible operation of multiple robotic manipulators in a shared workspace requires an online trajectory planning with static and dynamic collision avoidance. In this work, we propose a real-time capable motion control algorithm, based on non-linear model predictive control, which accounts for static and dynamic collision avoidance. The proposed algorithm is formulated as a non-cooperative game, where each robot is considered as an agent. Each agent optimizes its own motion and accounts for the predicted movement of surrounding agents. We propose a novel approach to formulate the dynamic collision constraints. Additionally, we account for deadlocks that might occur in a setup of multiple robotic manipulators. We validate our algorithm on a pick and place scenario for four collaborative robots operating in a common workspace in the simulation environment Gazebo. The robots are controlled by the Robot Operating System (ROS). We demonstrate, that our approach is real-time capable and, due to the distributed nature of the approach, easily scales to an arbitrary number of robot manipulators in a shared workspace.

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“…B. über Platt formen angeboten werden [SB16b]. Eine Möglichkeit, Unternehmen individuell zur Produktion eines Bauteils zu vernetzen, basiert auf dem Konzept ProduktionsDienstleistungen auf digi talen Marktplätzen anzubieten und wird als Production as a Service (PaaS) bezeichnet [He20].…”

Section: Introductionunclassified

Modellierung von Dienstleistungen, Capabilities und Skills zur Einbindung von Unternehmen in eine marktplatzbasierte Fertigung

Volkmann

2024

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Diese Dissertation erläutert die Umsetzung eines RAMI 4.0 konformen Marktplatz in der spanenden Bearbeitung. Ziel ist es einen Lösungsansatz zu definieren, in dem firmenübergreifende Prozessketten für kleine Losgrößen automatisiert identifiziert werden und die Fertigung eines individuellen Produktes realisiert wird. Die Extraktion von Produktinformationen, die Fertigung eines individualisierten Produktes sowie die Beschreibung der Informationen in den Verwaltungsschalen wird validiert. Vor allem stellt sich als Herausforderung für die Zukunft heraus, eine gemeinsame Semantik für die Beschreibung von Capabilities zu definieren. Diese würde ermöglichen, dass ein Matching zwischen proprietären Produktinformationen und Skills möglich wird. Inhaltsverzeichnis Danksagung III Kurzfassung VII Abstract VIII 1 Einleitung 1 1.1 Motivation und Problemstellung . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Zielsetzung und Forschungsfragen . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Vorgehensweise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2 Grundlagen und Stand der Technik 7 2.1 Produktions und Steuerungssysteme . . . ....

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Considering interdependencies for a dynamic generation of process chains for Production as a Service

Cited by 11 publications

References 11 publications

Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators

Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators

Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game

Modellierung von Dienstleistungen, Capabilities und Skills zur Einbindung von Unternehmen in eine marktplatzbasierte Fertigung

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