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Abstract. The development of autonomous vehicle systems demands the increased usage of software based control mechanisms. Generally, this leads to very complex systems, whose proper functioning has to be ensured. In our work we aim at investigating and assessing the potential effects of software issues on the safety, reliability and availability of complex embedded autonomous systems. One of the key aspects of the research concerns the mapping of functional descriptions in form of integrated behavior-based control networks to State-Event Fault Tree models.

Abstract. We present a user-assisted approach to extracting and visualizing structural features from point clouds obtained by terrestrial and airborne laser scanning devices. We apply a multi-scale approach to express the membership of local point environments to corresponding geometric shape classes in terms of probability. This information is filtered and combined to establish feature graphs which can be visualized in combination with the color-encoded feature and structural probability estimates of the measured raw point data. Our method can be used, for example, for exploring geological point data scanned from multiple viewpoints.

We present a virtual-reality framework for the continuous improvement process (CIP) of industrial production lines. In contrast to the conventional CIP workshop, our framework facilitates the implementation and validation of proposed modifications of the (virtual) production environment during the workshop whereas the results are immediately visible. The core concept of our framework is a product assembly graph from which a computer-animated representation is derived. The latter can be exported into a VRML2-animation for display on immersive VR systems. Interactive tools allow the modification of the assembly graph, making these modifications and their impact immediately visible.