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Today's mobile robotic systems are expected to handle a great variety of different tasks while reliably operating in highly complex and dynamic environments. This requires a correct and interpretable representation of the robot's surroundings. In recent years, a number of world representations have been developed, tailored for specific fields of application, but with very poor generalization possibilities. In this paper, we close the gap between application-specific world models by introducing a more holistic approach to environment modeling in the form of a Contextual Object-based Representation of the Environment. It is composed of a set of state vectors combining object semantics and the key concepts of the different world modeling techniques into a high-level object-oriented representation. The structure enables the probabilistic modeling of complex and dynamic environments together with all associated …