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Conference papers

Attention-Based Navigation in Human-Populated Environments

Thierry Fraichard 1 Patrick Reignier 1 Carlos Di Pietro 1
1 PRIMA - Perception, recognition and integration for observation of activity
Inria Grenoble - Rhône-Alpes, UJF - Université Joseph Fourier - Grenoble 1, INPG - Institut National Polytechnique de Grenoble , CNRS - Centre National de la Recherche Scientifique : UMR5217
Abstract : Assistant robots and robot companions are service robots designed to share the human living space, to navigate among and interact with human beings. From the mobility point of view, roboticists have recently striven to develop navigation scheme geared towards achieving so-called "socially acceptable motions". To that end, various concepts borrowed from environmental psychology and anthropology have been used, the Personal Space concept from Proxemics being perhaps the most widely used. The purpose of this work here is to further the research in this area by taking into account other factors such as human activities, interaction configurations and intentions. To that end, an attentional model [Maisonnasse 06] derived from cognitive psychology is used to dynamically determine the different interactions taking place between the entities, i.e. robot, persons and objects, that are present in the environment. The attention of a given person is modeled as a 3D vector whose norm is the amount of attentional resources that the person has. The vector direction is the main attentional direction around which the attentional resources of the person are spread. How attention is spread depends on the salience, i.e. the ability to attract the attention, of the entities at hand. Computing this vector for every entity in the environment yields the corresponding attentional matrix. Each matrix line gives the amount of attention that a particular person gives to the other entities whereas a matrix column gives the amount of attention globally received by an entity. This matrix dynamically changes depending on the current situation. Now, it will be shown how the robot can use this attention information in order to decide its future course of action depending on the task at hand. It could for instant seek to attract one person's attention or, on the contrary, to minimize the distraction caused.
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Submitted on : Friday, September 13, 2013 - 3:55:37 PM
Last modification on : Tuesday, February 9, 2021 - 3:24:36 PM


  • HAL Id : hal-00861840, version 1



Thierry Fraichard, Patrick Reignier, Carlos Di Pietro. Attention-Based Navigation in Human-Populated Environments. Israeli Conference on Robotics, Nov 2013, Tel Aviv, Israel. ⟨hal-00861840⟩



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