Browsing by Author "Kraus, Werner"

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Open Access
Einfluß des naturnahen Gewässerausbaus auf den Geschiebetransport
(1993) Wieprecht, Silke; Kraus, Werner
Nach einem naturnahen Ausbau des Unterlaufs der Weißach, einem Wildbach und Hauptzufluß des Tegernsees, lagerten sich beim Durchlauf einer Hochwasserwelle im Bereich eines Gefälleknicks große Geschiebemengen ab. In einem hydraulischen Modell mit beweglicher Sohle (Maßstab 1:20) wurden die vorhandenen Bedingungen und mögliche Verbesserungen zur Verhinderung von Auflandungen untersucht. Weiterhin wurden grundsätzliche Untersuchungen über den Einfluß von Sohleinbauten auf den Geschiebetransport und die Wassertiefen durchgeführt.
Open Access
Force control of cable-driven parallel robots
(2016) Kraus, Werner; Pott, Andreas (Junior-Prof. Dr.-Ing.)
In this thesis, a relatively new class of robots which use cables instead of rigid links is investigated. As cable can transmit only pull forces, cable robots make high demands on the control. The cable robots investigated in this thesis have more cables than degrees-offreedom of the platform and, thus, belong to the class of redundant robots. The redundancy allows to tense the cables agairrst each other. A control approach for synchronaus control of the platform position and the cable forces is proposed. For this purpose, system identifications for dynamic models of the robot are carried out and the forward kinematics is expanded to deal with non-linear cable stiffness. The proposed approach for calculation of the desired cable forces allows for step-less adjustment of the internal tensions. The investigations show that with change of the internal tension the eigenfrequencies of the robot can be influenced by 15-30%. By choice of a minimal tension Ievel, the energy consumption of the robot can be decreased by up to 20% while the performance of the robot remains on the same Ievel. For the proposed control scheme, extensive investigations of the positional accuracy are carried out. As reference approach, the control assuming a rigid robot model without closed-loop control of the operational space position and cable forces is used. The two approaches delivered comparable results in the workspace centre. The position accuracy with a payload of 80 kg amounted to roughly 70 mm and 2.5°. Using the proposed controller at the workspace border, almost the same accuracy could be reached as weil, as the cables are kept under tension. For rnachining processes like grinding, the well-known hybrid position and force control approach is incorporated on a cable robot. With the control approach, the robot can apply a contact force in a programmable direction, while the platform can be position-controlled in the Iasting directions. For the human robot cooperation, an admittance controller is proposed. The platform simulates a virtual spring-mass-damper system which enables for the implementation of a virtual workspace. With the demonstrator, a bandwidth of 13Hz is reached.
Open Access
A survey on learning-based robotic grasping
(2020) Kleeberger, Kilian; Bormann, Richard; Kraus, Werner; Huber, Marco F.
This review provides a comprehensive overview of machine learning approaches for vision-based robotic grasping and manipulation. Current trends and developments as well as various criteria for categorization of approaches are provided. Model-free approaches are attractive due to their generalization capabilities to novel objects, but are mostly limited to top-down grasps and do not allow a precise object placement which can limit their applicability. In contrast, model-based methods allow a precise placement and aim for an automatic configuration without any human intervention to enable a fast and easy deployment. Both approaches to robotic grasping and manipulation with and without object-specific knowledge are discussed. Due to the large amount of data required to train AI-based approaches, simulations are an attractive choice for robot learning. This article also gives an overview of techniques and achievements in transfers from simulations to the real world.
Open Access
Towards scalability for resource reconfiguration in robotic assembly line balancing problems using a modified genetic algorithm
(2024) Albus, Marcel; Hornek, Timothée; Kraus, Werner; Huber, Marco F.
Assembly lines are still one of the most used manufacturing systems in modern-day production. Most research affects the building of new lines and, less frequently, the reconfiguration of existing lines. However, the first is insufficient to meet the reconfigurable production paradigm required by volatile market demands. Consequent reconfiguration of resources by production requests affects companies’ competitiveness. This paper introduces a problem-specific genetic algorithm for optimizing the reconfiguration of a Robotic Assembly Line Balancing Problem with Task Types, including additional company constraints. First, we present the greenfield and brownfield optimization objectives, then a mathematical problem formulation and the composition of the genetic algorithm. We evaluate our model against an Integer Programming baseline on a reconfiguration dataset with multiple equipment alternatives. The results demonstrate the capabilities of the genetic algorithm for the greenfield case and showcase the possibilities in the brownfield case. With a scalability improvement through computation time decrease of up to ∼2.75 ×, reduced number of equipment and workstations, but worse objective values, the genetic algorithm holds the potential for reconfiguring assembly lines. However, the genetic algorithm has to be further optimized for the reconfiguration to leverage its full potential.