3D Computer-based animations are nowadays used for training purposes in a wide range of industrial applications like assembly, maintenance and operations. Authoring them is usually a time consuming task, demanded to professional 3D designers, who need at first a good understanding of the involved entities and actions in order to create customized animations.The proposed methodology deals with the use of an ontology in order to filter and understand generic natural language training requests. Once identified the proper actors and actions, they are associated to the corresponding models and movements to be performed in the virtual environment and translated in a 3D graphics format template. The result is a customized animation, which can be created by a non-expert designer and then visualized by the worker on site.The role of the ontology is to reduce the overall complexity of the animation authoring process by assuring the necessary comprehension of the training requests as well as reusability and extensibility of the structure of both modeled objects and of animations' components in different fields of knowledge.
Modern automobiles contain more and more mechatronical components to support the task of driving. Such mechatronical components are, e.g., an anti-lock braking system (ABS) and an electronic stability program (ESP) to support driving safety, or a predictive advanced front lighting system P-AFS) to enhance the lighting capabilities of a vehicle on a winding road. P-AFS uses GPS-data to locate the vehicle’s position plus digital map data to predict the curvature of the road in front of the vehicle. Based on this, P-AFS predicts the road scenario and swivels the front headlights accordingly. That way, the headlights follow the road’s curvature and optimally illuminate the road in front of the vehicle. To design, evaluate, and optimize the control algorithms within the electronic control unit (ECU) of the P-AFS component, up to 30 design variables need to be adjusted and tuned to ensure an optimal response of the system to the current road scenario. For this task, numerous time-consuming and costly test drives at night are necessary. This paper introduces a Virtual Reality-based night drive simulator that visualizes the complex lighting characteristics of automotive headlights in high detail and in real-time on a PC-based system. The user drives a simulated vehicle over a virtual test track at night, the vehicle’s motion directly influences the lighting direction of headlights, and the effect of the vehicle dynamics on the lighting can be evaluated directly in the simulator. The system is connected to the control algorithms of a P-AFS component to control the headlights swivelling for a close-to-reality simulation of a P-AFS based lighting system during the simulated night drive. That way, good combinations of the design variables can be found, based on virtual night drives in the simulator system, and the number of real test drives can be reduced significantly. Promising combinations of the design variables then can be validated in a test vehicle during a real test drive a night.
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