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This paper proposes a quality of service multi-sensor bootstrap filter for automated driving that deals with time-varying or state dependent conditions. In this way, the reliability of the sensor data fusion system is continuously evaluated in order to detect potentially dangerous conditions such as sensor failure or adverse environmental conditions such as rain and fog. Simulations show that the...
This paper presents a systematic approach to evaluate the tracking performance limits for different sensor modalities (lidar, radar and vision) and for combination of these sensors modalities. The Cramer-Rao lower bound (CRLB) is used to predict the tracking performance limits for state of the art sensors such as the Continental ARS408 radar, Velodyne HDL-64E lidar and a state of the art monocular/stereo...
In this paper, we introduce a non-verbal multimodal joint visual attention model for human-robot interaction in household scenarios. Our model combines the bottom-up saliency and depth-based segmentation with the top-down cues such as pointing and gaze to detect the objects of interest according to the user. For generation of the top-down saliency maps, we have introduced novel methods for object...
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