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- W2909475206 abstract "This paper presents a new model to make robots capable of approaching and engaging people with a human-like behavior, while they are walking in a side-by-side formation with a person. This method extends our previous work [1], which allows the robot to adapt its navigation behaviour according to the person being accompanied and the dynamic environment. In the current work, the robot is able to predict the best encounter point between the human-robot group and the approached person. Then, in the encounter point the robot modifies its position to achieve an engagement with both people. The encounter point is computed using a gradient descent method that takes into account all people predictions. Moreover, we make use of the Extended Social Force Model (ESFM), and it is modified to include the dynamic goal. The method has been validated over several situations and in real-life experiments, in addition, a user study has been realized to reveal the social acceptability of the robot in this task." @default.
- W2909475206 created "2019-01-25" @default.
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- W2909475206 date "2018-10-01" @default.
- W2909475206 modified "2023-10-17" @default.
- W2909475206 title "Robot Approaching and Engaging People in a Human-Robot Companion Framework" @default.
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- W2909475206 doi "https://doi.org/10.1109/iros.2018.8594149" @default.
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