Object-based World Modeling in Semi-Static Environments with Dependent Dirichlet-Process Mixtures

To accomplish tasks in human-centric indoor environments, robots need to represent and understand the world in terms of objects and their attributes. We refer to this attribute-based representation as a world model, and consider how to acquire it via noisy perception and maintain it over time, as objects are added, changed, and removed in the world... (read more)

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