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Multimodal attention is a key requirement for humanoid robots in order to navigate in complex environments and act as social, cognitive human partners. To this end, robots have to incorporate attention mechanisms that focus the processing on the potentially most relevant stimuli while controlling the sensor orientation to improve the perception of these(More)
The perception of the environment using opto-acoustic scene analysis techniques [1] is an extremely important and challenging task for humanoid robots. Thereby, the acquisition of visual and acoustic information provides the basis of the perception and enables the robot to interact with humans and to assist in everyday tasks. Another step is the exploration(More)
The opto-acoustic scene analysis is an extremely important as well as a challenging task for a humanoid robot. By the opto-acoustic scene analysis, the guided and autonomous exploration of the environment by means of acoustic and/or visual perception is meant. On the one hand, the perception ability is necessary to interact with humans in a humanoid way. On(More)
We extend our work on an integrated object-based system for saliency-driven overt attention and knowledge-driven object analysis. We present how we can reduce the amount of necessary head movement during scene analysis while still focusing all salient proto-objects in an order that strongly favors proto-objects with a higher saliency. Furthermore, we(More)
In this paper, investigations regarding the robust classification of acoustically observable sources (kitchen appliances and speakers) are presented. Thereby, two deciding factors are considered. On the one hand, the data acquisition should be exclusively done by the on-board sensors of the robot. On the other side, the entire information processing must be(More)
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