Ruth Schulz

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– RatSLAM is a biologically-inspired visual SLAM and navigation system that has been shown to be effective indoors and outdoors on real robots. The spatial representations at the core of RatSLAM, the pose cells, form in a distributed fashion as the robot learns the environment. The activity in the pose cells, while being coherent, does not possess strong(More)
— In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot without environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with(More)
(2015) Robot navigation using human cues: A robot navigation system for symbolic goal-directed exploration. Notice: Changes introduced as a result of publishing processes such as copy-editing and formatting may not be reflected in this document. For a definitive version of this work, please refer to the published source: Abstract— In this paper we present(More)