References

siMLPe

Guo, W., Du, Y., Shen, X., Lepetit, V., Alameda-Pineda, X., & Moreno-Noguer, F. (2022, July 4). Back to MLP: a simple baseline for human motion prediction. arXiv.org. https://arxiv.org/abs/2207.01567

AndyDataset

Maurice P., Malaisé A., Amiot C., Paris N., Richard G.J., Rochel O., Ivaldi S. « Human Movement and Ergonomics: an Industry-Oriented Dataset for Collaborative Robotics ». The International Journal of Robotics Reserach, Volume 38, Issue 14, Pages 1529-1537.

TeleopIcub Dataset

Penco, L., Mouret, J., & Ivaldi, S. (2021, July 2). Prescient teleoperation of humanoid robots. arXiv.org. https://arxiv.org/abs/2107.01281

H36M Dataset

Human3.6M: Large scale datasets and predictive methods for 3D human sensing in natural environments. (n.d.). IEEE Journals & Magazine | IEEE Xplore. https://ieeexplore.ieee.org/document/6682899

On the Continuity of Rotation Representations in Neural Networks

Zhou, Y., Barnes, C., Lu, J., Yang, J., & Li, H. (2018, December 17). On the Continuity of Rotation Representations in Neural Networks. arXiv.org. https://arxiv.org/abs/1812.07035

ProMPs

Paraschos, Alexandros & Daniel, Christian & Peters, Jan & Neumann, Gerhard. (2018). Using probabilistic movement primitives in robotics. Autonomous Robots. 42. 10.1007/s10514-017-9648-7.