Abstract
We built a model of the environment for human–robot interaction by learning from humans cognitive processes. Our method, which differs from previous map building techniques in terms of perspectives, is based on a route perspective that is a mental tour of the environment. The main contribution of this work is the theory and computational implementation of the concept of route with its respective visual memory. The concept of route is modeled as a three layered model composed of memory layer, survey layer and route layer. By imitating the human concept of a route, the route layer is modeled as a directional path segmented by action taking associated with visual memory taken while traveling the path. We developed a system that generates human understandable route directions which was evaluated towards two methods: one copied from the explanation of a human expert and one generated with a model without the route perspective layer. Finally, experimental results demonstrate the usefulness of the route perspective layer, since it performed better than the model without the route layer and similarly to the human expert.
















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This research was supported by the Ministry of Internal Affairs and Communications of Japan.
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This paper is an extended version of conference paper [1], with integrated technical details, additional discussions between our proposal and existing cognitive map literature; we added more participants for our experiments and added explanations in the experimental and conclusion sections.
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Morales, Y., Satake, S., Kanda, T. et al. Building a Model of the Environment from a Route Perspective for Human–Robot Interaction. Int J of Soc Robotics 7, 165–181 (2015). https://doi.org/10.1007/s12369-014-0265-8
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DOI: https://doi.org/10.1007/s12369-014-0265-8