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Method for Bottle Opening with a Dual-Arm Robot.

Francisco J Naranjo-Campos1, Juan G Victores1, Carlos Balaguer1

  • 1RoboticsLab, Systems and Automation Engineering Department, University Carlos III of Madrid, 28911 Leganés, Spain.

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Summary

This study presents a novel robotic system for bottle opening, aiding individuals with disabilities. The dual-arm robot TIAGo++ uses vision, manipulation, and deep reinforcement learning for effective assistance.

Keywords:
assistive technology and rehabilitation engineeringautonomous robotic systemsmachine learningperception and sensingposition and force controlreinforcement learning controlrobot manipulators

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Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Artificial Intelligence

Background:

  • Individuals with injuries or disabilities often require assistance with daily manipulation tasks.
  • Robotic assistance can significantly enhance independence and quality of life.

Purpose of the Study:

  • To develop and validate a robotic method for automated bottle opening using a dual-arm robot.
  • To enhance accessibility for individuals needing help with common tasks.

Main Methods:

  • Utilized the TIAGo++ dual-arm robot with an RGB-D camera for vision-based object detection.
  • Implemented a control scheme combining position, force control, and Deep Reinforcement Learning (DRL) for manipulation.
  • Planned safe trajectories for grasping and unscrewing actions.

Main Results:

  • Successfully trained a Deep Reinforcement Learning agent for precise gripper rotation control.
  • Demonstrated effective bottle opening through coordinated dual-arm manipulation and force feedback.
  • Validated the system's practical viability in experimental settings.

Conclusions:

  • The proposed robotic approach effectively automates bottle opening, enhancing accessibility.
  • Integration of vision, manipulation, and DRL offers a robust solution for assistive robotics.
  • The TIAGo++ robot shows promise for real-world applications in aiding individuals with limited mobility.