@Article{carpentier:tro:2016,
  author    = {Carpentier, Justin and Benallegue, Mehdi and Mansard, Nicolas and Laumond, Jean-Paul},
  title     = {Center of Mass Estimation for Polyarticulated System in Contact - A Spectral Approach},
  journal   = {IEEE Transactions on Robotics},
  year      = {2016},
  volume    = {32},
  number    = {4},
  pages     = {810--822},
  month     = {August},
  doi       = {10.1109/TRO.2016.2572680},
  url       = {https://hal.archives-ouvertes.fr/hal-01182734/file/15\_tro\_com\_estimation.pdf},
  keywords  = {Estimation, Humanoid robots, Robot sensing systems, Dynamics, Solid modeling},
  abstract  = {This paper discusses the problem of estimating the position of the center of mass for a polyarticulated system (e.g., a humanoid robot or a human body), which makes contact with its environment. The only sensors providing measurements on this point are either interaction force sensors or kinematic reconstruction applied to a dynamic model of the system. We first study the observability of the center-of-mass position using these sensors and we show that the accuracy domain of each measurement can be easily described through a spectral analysis. We finally introduce an original approach based on the theory of complementary filtering to efficiently merge these input measurements and obtain an estimation of the center-of-mass position. This approach is extensively validated in simulations by using a model of a humanoid robot through which we confirm the spectral analysis of the signal errors and show that the complementary filter offers a lower average reconstruction error than the classical Kalman filter. Some experimental applications of this filter on real signals are also presented.},
  publisher = {IEEE-INST Electrical Electronics Engineers Inc},
  address   = {445 Hoes Lane, Piscataway, NJ 08855-4141, USA}
}