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GPI based velocity/force observer design for robot manipulators.

Alejandro Gutiérrez-Giles1, Marco A Arteaga-Pérez1

  • 1Departamento de Control y Robótica, DIE, Facultad de Ingeniería, Universidad Nacional Autónoma de México, Apdo. Postal 70-256, México, D. F., 04510, Mexico.

ISA Transactions
|May 1, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a novel Generalized Proportional Integral (GPI) observer to estimate robot joint velocities and contact forces using only position measurements, eliminating the need for costly force sensors.

Keywords:
GPI techniqueRobot force controlVelocity/force observers

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Area of Science:

  • Robotics
  • Control Systems
  • Mechatronics

Background:

  • Robotic manipulation requires precise control of interaction forces with the environment.
  • Traditional force sensing methods using sensors can be expensive, prone to noise, and have limited bandwidth.
  • Alternative methods are needed to estimate interaction forces effectively.

Purpose of the Study:

  • To propose a velocity/force observer based on the Generalized Proportional Integral (GPI) technique.
  • To estimate joint velocities and contact forces using only position measurements.
  • To enable force/position control schemes without relying on physical force sensors.

Main Methods:

  • Development of a velocity/force observer utilizing the Generalized Proportional Integral (GPI) technique.
  • Estimation of joint velocities and contact forces solely from position measurements.
  • Formal mathematical proof of the ultimate boundedness of observation errors.

Main Results:

  • Successful estimation of joint velocities and contact forces using the proposed GPI observer.
  • Demonstration that arbitrarily small ultimate bounds for observation errors can be achieved.
  • Validation of the observer's effectiveness through simulation results.

Conclusions:

  • The proposed GPI-based observer offers a viable alternative to traditional force sensors in robotic applications.
  • This method effectively estimates interaction forces and joint velocities, enhancing control capabilities.
  • The approach provides a robust and accurate solution for robot-environment interaction control.