Hochschule Ravensburg-Weingarten
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Robotic grasping has been a prevailing problem ever since humans began creating robots to execute human-like tasks. The problems are usually due to the involvement of moving parts and sensors. Inaccuracy in sensor data usually leads
to unexpected results. Researchers have used a variety of sensors for improving manipulation tasks in robots.
This thesis focuses specifically on grasping unknown objects using mobile service robots. An approach using convolutional neural networks to generate grasp points
in a scene using RGBD sensor data is proposed. Two neural networks that perform grasp detection in a top down scenario are evaluated, enhanced and compared in
a more general scenario. Experiments are performed in a simulated environmentas well as the real world.
The results are used to understand how difference in
sensor data can affect grasping and enhancements are made to overcome these effects and to optimize the solution.
This thesis is an improvement on the works of Douglas Morrison, Peter Corke and Jürgen Leitner in their work Closing the Loop for Robotic Grasping: A Real-time,
Generative Grasp Synthesis Approach and Fu-Jen Chu, Ruinian Xu and Patricio A. Vela in their work Real-world Multi-object, Multi-grasp Detection.
The requirement of air conditioning in modern passenger cars need to fullfill enviromental standards with respect to refrigerant concerning global warming potential and ozone depletion with flour chlor carbon hydrogen mixtures.
This leads to compromises with respect to energy onsumption and cost of components.
As an alternative to standard refrigeration cycles, an inexpensive direct air cooling process is presented and discussed with respect to performance.
The process is specially suited for electric vehicles or vehicles equipped with an electric boosting device (E-charger).
Es werden 1428 im Jahr 2013 verfügbare Neufahrzeugtypen hinsichtlich des
CO2-Ausstoßes und der Fahrzeugparameter analysiert.
Die gewonnenen Daten werden mit der CO2-Klassifizierung
nach der PKW-EnVKV sowie den
CO2-Flottenzielvorgaben nach EU-Verordnung 443/2009 verglichen.
Unter Verwendung dimensionsanalytischer Methoden wird der
Zusammenhang zwischen Kraftstoffverbrauch, Fahrzeugparametern
wie Fahrzeugmasse, Höchstgeschwindigkeit und Beschleunigung
aufgezeigt und physikalisch begründet.
Durch Analyse der Kennzahlen lassen sich Fahrzeugtypen
und Technologien mit hohem spezifischen Verbrauch identifizieren. Es
wird deutlich, welche Technologien zu geringen spezifischen Verbräuchen
führen.
Die dimensionslosen Kennzahlen werden verwendet, um eine Abschätzung
des Kraftstoffverbrauchs von Fahrzeugen nach heutigem Technologiestand
zu machen.