@InProceedings{grimm:humanoids:2018,
  author    = {Grimm, Raphael and Kheddar, Abderrahmane and Asfour, Tamim},
  title     = {Generation of Walking Motions Based on Whole-Body Poses and QP control},
  booktitle = {IEEE-RAS International Conference on Humanoid Robots},
  year      = {2018},
  pages     = {510--515},
  address   = {Beijing,China},
  month     = {November 6-November 9},
  url       = {https://h2t.anthropomatik.kit.edu/pdf/Grimm2018.pdf},
  doi       = {https://doi.org/10.1109/HUMANOIDS.2018.8624913},
  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.}
}