On Leader Following and Classification

Abstract : Service and assistance robots that must move in human environment must address the difficult issue of navigating in dynamic environments. As it has been shown in previous works, in such situations the robots can take advantage of the motion of persons by following them, managing to move together with humans in difficult situations. In those circumstances, the problem to be solved is how to choose a human leader to be followed. This work proposes an innovative method for leader selection, based on human experience. A learning framework is developed, where data is acquired, labeled and then used to train an AdaBoost classification algorithm, to determine if a candidate is a bad or a good leader, and also to study the contribution of features to the classification process.
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Communication dans un congrès
IROS 2014, Sep 2014, Chicago, United States. 2014
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Contributeur : Procópio Stein <>
Soumis le : mercredi 12 novembre 2014 - 10:45:41
Dernière modification le : mercredi 11 avril 2018 - 01:54:29

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Procópio Stein, Anne Spalanzani, Vitor Santos, Christian Laugier. On Leader Following and Classification. IROS 2014, Sep 2014, Chicago, United States. 2014. 〈hal-01069567v2〉

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