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Towards Automated Models of Activities of Daily Life

We propose automated probabilistic models of everyday activities (AM-EvA) as a novel technical means for the perception, interpretation, and analysis of everyday manipulation tasks and activities of daily life. AM-EvAs are based on action-related concepts in everyday activities such as action-related places (the place where cups are taken from the cupboard), capabilities (the objects that can be picked up single-handedly), etc. These concepts are probabilistically derived from a set of previous activities that are fully and automatically observed by computer vision and additional sensor systems. AM-EvA models enable robots and technical systems to analyze activities in the complete situation and activity context. They render the classification and the assessment of actions and situations objective and can justify the probabilistic interpretation with respect to the activities the concepts have been learned from. In this paper, we describe the current state of implementation of the system that realizes this idea of automated models of everyday activities and show example results from the observation and analysis of table setting episodes.