@InProceedings{shimizu:humanoids:2020,
  author    = {Shimizu, Soya and Ayusawa, Ko and Venture, Gentiane},
  title     = {Pseudo Direct and Inverse Optimal Control Based on Motion Synthesis Using FPCA},
  booktitle = {IEEE-RAS International Conference on Humanoid Robots},
  year      = {2021},
  address   = {Munich, Germany},
  month     = {July 19-July 21},
  url       = {https://ieeexplore.ieee.org/document/9555773},
  keywords  = {Optimization and Optimal Control, Human and Humanoid Motion Analysis and Synthesis, Whole-Body Motion Planning and Control},
  doi       = {10.1109/HUMANOIDS47582.2021.9555773},
  abstract  = {This paper presents a method to estimate cost weights of cost functions and complex multiple joint motion time-series values of humanoid robots easily, using functional principal component analysis (FPCA) instead of direct optimal control (DOC) and inverse optimal control (IOC). Each given object\textquotesingle s cost weight exemplar can be converted into a point in the FPC space by applying FPCA. Cost weight and the FPC textcolorblackspace enable to synthesize the motion model data and the cost function factor and therefore versatile motion data conveniently. The proposed method surpasses classic DOC and IOC methods in terms of calculation time and efficiency, in novel data analysis. The proposed method is applied to the humanoid robot HRP4, to generate arm motions, and proves the concept with some cost functions. Finally, the accuracy of the motion generation is confirmed.}
}