Methods representing space suitable to learning, semantic concept and the relation to human cognitive capabilities (original) (raw)

AI-generated Abstract

The research focuses on developing a hierarchical representation and cognitive mapping of space to assist robots in home navigation tasks. It emphasizes the fusion of topological, metric, and semantic information, while exploring how these spatial concepts can be effectively learned and represented. The paper draws parallels between human cognitive capabilities and robotic representations of space, aiming to enhance the interaction between humans and robots through intuitive interfaces.

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