IROS 2022poster2 citations

Robust Cartesian Kinematics Estimation for Task-Space Control Systems

Seyed Ali Baradaran Birjandi, Niels Dehio, Abderrahmane Kheddar, Sami Haddadin

Abstract

We discuss a novel method for estimating task Cartesian position and velocity in robot manipulators. This is done by model-based fusion of inertial measurement units with motor encoders. The model is developed to robustly handle the uncertainties in the trajectory. Thus, not only the approach benefits from high fidelity and bandwidth thanks to multiple-sensory fusion, but it also enforces stability despite poorly formulated motions. This empowers the method to be utilized in complex closed-loop applications, where both task position and velocity information is required.

BibTeX
@inproceedings{iros2022_robustcartesiank,
  title = {Robust Cartesian Kinematics Estimation for Task-Space Control Systems},
  author = {Seyed Ali Baradaran Birjandi and Niels Dehio and Abderrahmane Kheddar and Sami Haddadin},
  booktitle = {IROS 2022},
  year = {2022}
}
Robust Cartesian Kinematics Estimation for Task-Space Control Systems · IROS 2022