@Article{ayusawa:tro:2017,
  author    = {Ayusawa, Ko and Yoshida, Eiichi},
  title     = {Motion Retargeting for Humanoid Robots Based on Simultaneous Morphing Parameter Identification and Motion Optimization},
  journal   = {IEEE Transactions on Robotics},
  year      = {2017},
  volume    = {33},
  number    = {6},
  pages     = {1343--1357},
  month     = {December},
  doi       = {10.1109/TRO.2017.2752711},
  url       = {https://staff.aist.go.jp/k.ayusawa/pdf/Ayusawa\_2017\_TRO.pdf},
  keywords  = {Human motion capturing, humanoid robot, identification, motion retargeting, optimization},
  abstract  = {Abstract\textemdash This paper presents a novel method for retargeting 
human motions onto a humanoid robot. The method solves the
following three simultaneous problems: the geometric parameter
identification that morphs the human model to the robot model,
motion planning for a robot, and the inverse kinematics of the human
motion-capture data. Simultaneous solutions can imitate the
original motion more accurately than conventional approaches,
which solve the problems sequentially. The proposed method can
reconstruct the human motion within the physical constraints imposed
by robot dynamics. A reconstruction step enables quantitative
analysis of the retargeting results through direct comparison
with the original human motion. The method can also provide the
precise morphing function as well as subject-specific models, which
can handle the different body dimensions of human subjects. This
new framework is suitable for applications that require an accurate
generation of human-likemotions with quantitative evaluation
criteria, such as humanoid robots that evaluate assistive devices.
Experimental tests of the proposed method were performed with
humanoid robot HRP-4.},
  publisher = {IEEE-INST Electrical Electronics Engineers Inc},
  address   = {445 Hoes Lane, Piscataway, NJ 08855-4141, USA}
}