Robust Cartesian Kinematics Estimation for Task-Space Control Systems

Seyed Ali Baradaran Birjandi, Niels Dehio, Abderrahmane Kheddar, and Sami Haddadin
Proceedings of 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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 multiplesensory 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.

@INPROCEEDINGS{Baradaran2022IROS,
  author=Baradaran Birjandi, Seyed Ali and Dehio, Niels and Haddadin, Sami and Abderrahmane Kheddar
  booktitle={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, 
  title={Robust cartesian kinematics estimation for task-space control systems}, 
  year={2022},
  volume={},
  number={},
  pages={},
  doi={}}