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Título

People's adaptive side-by-side model evolved to accompany groups of people by social robots

AutorRepiso, Ely CSIC ORCID; Garrell, Anaís CSIC ORCID ; Sanfeliu, Alberto CSIC ORCID
Fecha de publicación2020
EditorInstitute of Electrical and Electronics Engineers
CitaciónIEEE Robotics and Automation Letters 5: 2387-2394 (2020)
ResumenThe presented method implements a robot accompaniment in an adaptive side-by-side formation of a single person or a group of people. The method enhances our previous robot adaptive side-by-side behavior allowing the robot to accompany a group of people, not only one person. Adaptive means that the robot is capable to adjust its position and velocity to the behavior of the group being accompanied, without bothering other pedestrians in the environment, as well as facilitating the group navigation to avoid static and dynamic obstacles. Furthermore, the robot can deal with the random factor of human behavior in several situations. Firstly, if other people interfere in the path of the companions, the robot leaves space for the person of the group that has to avoid those other people, by approaching the other companion. Also, without invading any personal space. Secondly, if the people of the group changes their physical position inside the group formation, then the robot adapts to them dynamically by changing from the lateral position to the central position of the formation or otherwise. Thirdly, the robot adapts to changes in the velocity of people in the group and other people that interfere in the path of the group, in magnitude and orientation. Fourthly, the robot can deal with occlusions of one accompanied person by the other. The method has been validated using synthetic experiments and real-life experiments with our robot. Finally, we developed an user study comparing the method with a Wizard of Oz.
Versión del editorhttp://dx.doi.org/10.1109/LRA.2020.2970676
URIhttp://hdl.handle.net/10261/227719
DOI10.1109/LRA.2020.2970676
Identificadoresdoi: 10.1109/LRA.2020.2970676
e-issn: 2377-3766
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