Cognitive social zones for improving the pedestrian collision avoidance with mobile robots
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Redalyc
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| Formato: | Artículo científico |
| Lenguaje: | en |
| Publicado: |
Escuela Politécnica Nacional
2019
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| _version_ | 1876448393410117632 |
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| author | Daniel Herrera |
| author_facet | Daniel Herrera |
| contents | Cognitive social zones for improving the pedestrian collision avoidance with mobile robots Daniel Herrera Javier Gimenez Matias Monllor Flavio Roberti Ricardo Carelli Ingeniería Human proxemics social zones social robots robot cognition Social behaviors are crucial to improve the acceptance of a robot in human-shared environments. One of the most important social cues is undoubtedly the social space. This human mechanism acts like a repulsive field to guarantee comfortable interactions. Its modeling has been widely studied in social robotics, but its experimental inference has been weakly mentioned. Thereby, this paper proposes a novel algorithm to infer the dimensions of an elliptical social zone from a points-cloud around the robot. The approach consists of identifying how the humans avoid a robot during navigation in shared scenarios, and later use this experience to represent humans obstacles like elliptical potential fields with the previously identified dimensions. Thus, the algorithm starts with a first-learning stage where the robot navigates without avoiding humans, i.e. the humans are in charge of avoiding the robots while developing their tasks. During this period, the robot generates a points-cloud with 2D laser measures from its own framework to define the human-presence zones around itself but prioritizing its closest surroundings. Later, the inferred social zone is incorporated to a null-space-based (NSB) control for a non-holonomic mobile robot, which consists of both trajectory tracking and pedestrian collision avoidance. Finally, the performance of the learning algorithm and the motion control is verified through experimentation. 2019 artículo científico 1390-0129 https://www.redalyc.org/articulo.oa?id=688773632001 en http://www.redalyc.org/revista.oa?id=6887 Revista Politécnica application/pdf Escuela Politécnica Nacional Revista Politécnica (Ecuador) Num.2 Vol.42 |
| format | Artículo científico |
| id | redalyc_688773632001 |
| institution | Redalyc |
| language | en |
| publishDate | 2019 |
| publisher | Escuela Politécnica Nacional |
| spellingShingle | Cognitive social zones for improving the pedestrian collision avoidance with mobile robots Daniel Herrera Ingeniería Human proxemics social zones social robots robot cognition Cognitive social zones for improving the pedestrian collision avoidance with mobile robots Daniel Herrera Javier Gimenez Matias Monllor Flavio Roberti Ricardo Carelli Ingeniería Human proxemics social zones social robots robot cognition Social behaviors are crucial to improve the acceptance of a robot in human-shared environments. One of the most important social cues is undoubtedly the social space. This human mechanism acts like a repulsive field to guarantee comfortable interactions. Its modeling has been widely studied in social robotics, but its experimental inference has been weakly mentioned. Thereby, this paper proposes a novel algorithm to infer the dimensions of an elliptical social zone from a points-cloud around the robot. The approach consists of identifying how the humans avoid a robot during navigation in shared scenarios, and later use this experience to represent humans obstacles like elliptical potential fields with the previously identified dimensions. Thus, the algorithm starts with a first-learning stage where the robot navigates without avoiding humans, i.e. the humans are in charge of avoiding the robots while developing their tasks. During this period, the robot generates a points-cloud with 2D laser measures from its own framework to define the human-presence zones around itself but prioritizing its closest surroundings. Later, the inferred social zone is incorporated to a null-space-based (NSB) control for a non-holonomic mobile robot, which consists of both trajectory tracking and pedestrian collision avoidance. Finally, the performance of the learning algorithm and the motion control is verified through experimentation. 2019 artículo científico 1390-0129 https://www.redalyc.org/articulo.oa?id=688773632001 en http://www.redalyc.org/revista.oa?id=6887 Revista Politécnica application/pdf Escuela Politécnica Nacional Revista Politécnica (Ecuador) Num.2 Vol.42 |
| title | Cognitive social zones for improving the pedestrian collision avoidance with mobile robots |
| topic | Ingeniería Human proxemics social zones social robots robot cognition |
| url | https://www.redalyc.org/articulo.oa?id=688773632001 |