Refine
Year of publication
Document Type
- Conference Proceeding (1253)
- Article (reviewed) (687)
- Bachelor Thesis (604)
- Article (unreviewed) (566)
- Part of a Book (460)
- Contribution to a Periodical (287)
- Book (242)
- Master's Thesis (208)
- Other (142)
- Working Paper (105)
Conference Type
- Konferenzartikel (950)
- Konferenz-Abstract (156)
- Konferenzband (77)
- Sonstiges (42)
- Konferenz-Poster (32)
Language
- German (2867)
- English (1981)
- Other language (5)
- Russian (3)
- Multiple languages (2)
- French (1)
- Spanish (1)
Keywords
- Mikroelektronik (62)
- Digitalisierung (48)
- Marketing (47)
- Social Media (40)
- COVID-19 (37)
- E-Learning (35)
- RoboCup (33)
- Kommunikation (32)
- Künstliche Intelligenz (32)
- Dünnschichtchromatographie (29)
Institute
- Fakultät Maschinenbau und Verfahrenstechnik (M+V) (1118)
- Fakultät Medien und Informationswesen (M+I) (bis 21.04.2021) (1103)
- Fakultät Elektrotechnik und Informationstechnik (E+I) (bis 03/2019) (917)
- Fakultät Wirtschaft (W) (650)
- Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) (565)
- Fakultät Medien (M) (ab 22.04.2021) (384)
- INES - Institut für nachhaltige Energiesysteme (245)
- ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik (161)
- Zentrale Einrichtungen (81)
- IMLA - Institute for Machine Learning and Analytics (79)
Open Access
- Closed Access (1708)
- Open Access (1693)
- Closed (756)
- Bronze (345)
- Diamond (92)
- Gold (77)
- Hybrid (50)
- Grün (16)
For the RoboCup Soccer AdultSize League the humanoid robot Sweaty uses a single fully convolutional neural network to detect and localize the ball, opponents and other features on the field of play. This neural network can be trained from scratch in a few hours and is able to perform in real-time within the constraints of computational resources available on the robot. The time it takes to precess an image is approximately 11 ms. Balls and goal posts are recalled in 99 % of all cases (94.5 % for all objects) accompanied by a false detection rate of 1.2 % (5.2 % for all). The object detection and localization helped Sweaty to become finalist for the RoboCup 2017 in Nagoya.
One of the challenges in humanoid robotics is motion control. Interacting with humans requires impedance control algorithms, as well as tackling the problem of the closed kinematic chains which occur when both feet touch the ground. However, pure impedance control for totally autonomous robots is difficult to realize, as this algorithm needs very precise sensors for force and speed of the actuated parts, as well as very high sampling rates for the controller input signals. Both requirements lead to a complex and heavy weight design, which makes up for heavy machines unusable in RoboCup Soccer competitions.
A lightweight motor controller was developed that can be used for admittance and impedance control as well as for model predictive control algorithms to further improve the gait of the robot.
Comparing anomalies and exceptions to multilateral dysfunction across a number of spheres of world politics, the book chapter explores pathways through and beyond gridlock in trade. It provides a vital new perspective on world politics as well as a practical guide for positive change in global policy.
Risk aversion, financing and real servicThe Global CEO Survey was launched in 2015 by researchers from Offenburg University, the University of Westminster and the London School of Economics and Political Science (LSE) to better understand and discover what factors influence exporters’ demand for credit insurance. Although some scholars discussed aspects of corporate insurance demand with regard to exporters, there is limited research concerning the demand for export credit insurance associated with firm-specific factors. Only few empirical studies support existing theories on corporate insurance demand and export credits. This project investigates and fills the relevant gap of official export credit insurance demand.es
Quo Vadis Freihandel?
(2017)
In this paper we present the implementation of a model-predictive controller (MPC) for real-time control of a cable-robot-based motion simulator. The controller computes control inputs such that a desired acceleration and angular velocity at a defined point in simulator’s cabin are tracked while satisfying constraints imposed by working space and allowed cable forces of the robot. In order to fully use the simulator capabilities, we propose an approach that includes the motion platform actuation in the MPC model. The tracking performance and computation time of the algorithm are investigated in computer simulations. Furthermore, for motion simulation scenarios where the reference trajectories are not known beforehand, we derive an estimate on how much motion simulation fidelity can maximally be improved by any reference prediction scheme compared to the case when no prediction scheme is applied.
Micro gas turbines (MGTs) are regarded as combined heat and power (CHP) units which offer high fuel utilization and low emissions. They are applied in decentralized energy neration.
To facilitate the planning process of energy systems, namely in the context of the increasing application of optimization techniques, there is a need for easy-to-parametrize component models with sufficient accuracy which allow a fast computation. In this paper, a model is proposed where the non-linear part load characteristics of the MGT are linearized by means of physical insight of the working principles of turbomachinery. Further, it is shown that the model can be parametrized by the data usually available in spec sheets. With this model a uniform description of MGTs from several manufacturers
covering an electrical power range from 30kW to 333kW can be obtained. The MGT model was
implemented by means of Modelica/Dymola. The resulting MGT system model, comprising further heat exchangers and hydraulic components, was validated using the experimental data of a 65kW MGT from a trigeneration energy system.