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Generation of Walking Motions Based on Whole-Body Poses and QP Control

Raphael Grimm 1 Abderrahmane Kheddar 2 Tamim Asfour 1
2 IDH - Interactive Digital Humans
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Generating and executing whole-body motions for humanoid robots remains a challenging research question. In this paper, we present an approach that combines human motion data and QP-based control to generate humanoid motion. Following the contacts-before-motion paradigm, we first generate a sequence of stances based on our previous work on data-driven generation of whole-body multi-contact pose sequences from human motion data and their mapping to the target robot kinematics. In this paper, we address the next step of closed-loop execution of stance sequences based on QP controllers. We evaluated the approach in simulation on the humanoid robot ARMAR-4 and HRP4. The results show that our approach can successfully execute stance sequences generated by our previous work and thus the viability of learning locomotion patterns from human demonstrations.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-03131958
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Submitted on : Thursday, February 4, 2021 - 5:11:31 PM
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Raphael Grimm, Abderrahmane Kheddar, Tamim Asfour. Generation of Walking Motions Based on Whole-Body Poses and QP Control. IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), Nov 2018, Beijing, China. pp.510-515, ⟨10.1109/HUMANOIDS.2018.8624913⟩. ⟨lirmm-03131958⟩

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