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Human-robot cooperation for robust surface treatment using non-conventional sliding mode control.

J Ernesto Solanes1, Luis Gracia1, Pau Muñoz-Benavent1

  • 1Instituto de Diseño y Fabricación (IDF), Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022, Valencia, Spain.

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|June 25, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a human-robot collaboration method for surface treatment tasks. It uses two force sensors and adaptive control for precise robot guidance and task execution.

Keywords:
Cooperative taskForce feedbackSliding mode control

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Area of Science:

  • Robotics
  • Human-Robot Interaction
  • Control Systems Engineering

Background:

  • Surface treatment tasks like polishing and grinding require high precision.
  • Traditional methods often lack flexibility and adaptability in human-robot collaboration.
  • Integrating human guidance with robotic precision is challenging.

Purpose of the Study:

  • To develop a human-robot collaborative solution for surface treatment tasks.
  • To enable intuitive robot tool guidance by human operators.
  • To enhance the precision and efficiency of collaborative surface finishing operations.

Main Methods:

  • Implementation of a cooperative control scheme using two force sensors on the robot's end-effector and tool.
  • Utilizing a task priority-based approach for managing collaborative actions.
  • Employing adaptive non-conventional sliding mode control for robust performance.

Main Results:

  • Experimental validation using a 7R redundant manipulator (Sawyer cobot).
  • Demonstrated successful cooperative performance in tasks like polishing and grinding.
  • The system effectively integrates human guidance with automated robotic control.

Conclusions:

  • The proposed human-robot collaborative approach is effective for surface treatment.
  • The dual-force-sensor system and adaptive control enable precise and intuitive collaboration.
  • This method offers a viable solution for advanced robotic finishing applications.