English

DILIGENT-KIO: A Proprioceptive Base Estimator for Humanoid Robots using Extended Kalman Filtering on Matrix Lie Groups

Robotics 2021-06-01 v1

Abstract

This paper presents a contact-aided inertial-kinematic floating base estimation for humanoid robots considering an evolution of the state and observations over matrix Lie groups. This is achieved through the application of a geometrically meaningful estimator which is characterized by concentrated Gaussian distributions. The configuration of a floating base system like a humanoid robot usually requires the knowledge of an additional six degrees of freedom which describes its base position-and-orientation. This quantity usually cannot be measured and needs to be estimated. A matrix Lie group, encapsulating the position-and-orientation and linear velocity of the base link, feet positions-and-orientations and Inertial Measurement Units' biases, is used to represent the state while relative positions-and-orientations of contact feet from forward kinematics are used as observations. The proposed estimator exhibits fast convergence for large initialization errors owing to choice of uncertainty parametrization. An experimental validation is done on the iCub humanoid platform.

Keywords

Cite

@article{arxiv.2105.14914,
  title  = {DILIGENT-KIO: A Proprioceptive Base Estimator for Humanoid Robots using Extended Kalman Filtering on Matrix Lie Groups},
  author = {Prashanth Ramadoss and Giulio Romualdi and Stefano Dafarra and Francisco Javier Andrade Chavez and Silvio Traversaro and Daniele Pucci},
  journal= {arXiv preprint arXiv:2105.14914},
  year   = {2021}
}

Comments

Accepted to the IEEE International Conference on Robotics and Automation (ICRA) 2021

R2 v1 2026-06-24T02:39:28.398Z