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Robot assistance selection for large object manipulation with a human

Julie Dumora 1 Franck Geffard 1 Catherine Bidard 1 Nikos Aspragathos 2 Philippe Fraisse 3
1 DIASI - Département Intelligence Ambiante et Systèmes Interactifs
2 University of Patras [Patras]
3 IDH - Interactive Digital Humans
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : In this paper, we propose a method that allows a human to perform complex manipulation tasks jointly with a robotic partner. To that end, the robot has a library of assistances that it can provide for helping the human partner during a priori unknown collaborative tasks. According to the haptic cues naturally transmitted by the human partner, the robot selects on-line the suitable assistance for the current intended collaborative motion. Based on the naive bayes classifier and the Matthew Correlation Coefficient, the parameters of the decisionmaking are automatically tuned. An experiment on a real arm manipulator is provided to validate the proposed approach.
Keywords : Intent detection Large object comanipulation Manipulation task Naive Bayes classifiers Object manipulation Cybernetics Robots Correlation coefficient Collaborative tasks Assistive
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Conference papers
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https://hal-cea.archives-ouvertes.fr/cea-01841027
Contributor : Léna Le Roy <>
Submitted on : Tuesday, July 17, 2018 - 7:58:56 AM
Last modification on : Friday, June 25, 2021 - 9:48:06 AM

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CEA | CNRS | LIRMM | DRT | MIPS | UNIV-MONTPELLIER | LIST | IDH | GS-COMPUTER-SCIENCE

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Julie Dumora, Franck Geffard, Catherine Bidard, Nikos Aspragathos, Philippe Fraisse. Robot assistance selection for large object manipulation with a human. SMC: Systems, Man, and Cybernetics, Oct 2013, Manchester, United Kingdom. pp.1828-1833, ⟨10.1109/SMC.2013.315⟩. ⟨cea-01841027⟩

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