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Simulation-based physics reasoning for consistent scene estimation in an HRI context

Yoan Sallami 1 Séverin Lemaignan 2 Aurélie Clodic 3 Rachid Alami 1
1 LAAS-RIS - Équipe Robotique et InteractionS
LAAS - Laboratoire d'analyse et d'architecture des systèmes
3 LAAS-IDEA - Service Informatique : Développement, Exploitation et Assistance
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : Reasoning about spatial and geometric relations between objects in a tabletop human-robot interaction is a challenge due to the perception not being always consistent: objects placed on a table seem to be slightly in the air; they overlap; they disappear due to occlusions. Yet, interpreting and anchoring perceptual data in a physically consistent estimation of the scene is a crucial ability for humans, and thus robots in HRI context. In this paper we present a simulation-based physics reasoner integrated in a lightweight situation-assessment framework called Underworlds, that allows the robot to stabilize objects and build at run-time a consistent estimation of the scene, even for entirely hidden objects, while inferring the actions performed by its human partner.
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Yoan Sallami, Séverin Lemaignan, Aurélie Clodic, Rachid Alami. Simulation-based physics reasoning for consistent scene estimation in an HRI context. 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nov 2019, Macau, China. pp.7834-7841, ⟨10.1109/IROS40897.2019.8968106⟩. ⟨hal-02925945⟩

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