Authors
Jacob Goodman, Jinho Kim, Andrew S. Lee, S. Andrew Gadsden, Mohammad Al-Shabi
Corresponding Author
Jacob Goodman
Available Online 1 September 2017.
DOI
https://doi.org/10.2991/jrnal.2017.4.2.8How to use a DOI?
Keywords
Robotic manipulator, estimation theory, Kalman filter, smooth variable structure filter.
Abstract
Nonlinear estimation strategies are important for accurate and reliable control of robotic manipulators. This brief paper studies the application of estimation theory to a simple robotic manipulator. Two estimation techniques are considered: the classic extended Kalman filter (EKF), and the robust smooth variable structure filter (SVSF). The EKF is included to present a basic background in estimation techniques and the SVSF is described and implemented on the system. We simulate the SVSF applied to a dynamically modeled three-link robotic manipulator. The results of the paper demonstrate that nonlinear estimation techniques such as the SVSF can be applied effectively to robots with modeling uncertainty and external disturbances.

Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).