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Autonomous and Teleoperation Control of a Drawing Robot Avatar

Lingyun Chen, Abdeldjallil Naceri, Abdalla Swikir, Sandra Hirche, Sami Haddadin

TL;DR

The proposed control framework aims to improve bimanual robot telepresence quality by reducing the user workload and required prior knowledge through the automation of secondary or auxiliary tasks through the automation of secondary or auxiliary tasks.

Abstract

A drawing robot avatar is a robotic system that allows for telepresence-based drawing, enabling users to remotely control a robotic arm and create drawings in real-time from a remote location. The proposed control framework aims to improve bimanual robot telepresence quality by reducing the user workload and required prior knowledge through the automation of secondary or auxiliary tasks. The introduced novel method calculates the near-optimal Cartesian end-effector pose in terms of visual feedback quality for the attached eye-to-hand camera with motion constraints in consideration. The effectiveness is demonstrated by conducting user studies of drawing reference shapes using the implemented robot avatar compared to stationary and teleoperated camera pose conditions. Our results demonstrate that the proposed control framework offers improved visual feedback quality and drawing performance.

Autonomous and Teleoperation Control of a Drawing Robot Avatar

TL;DR

The proposed control framework aims to improve bimanual robot telepresence quality by reducing the user workload and required prior knowledge through the automation of secondary or auxiliary tasks through the automation of secondary or auxiliary tasks.

Abstract

A drawing robot avatar is a robotic system that allows for telepresence-based drawing, enabling users to remotely control a robotic arm and create drawings in real-time from a remote location. The proposed control framework aims to improve bimanual robot telepresence quality by reducing the user workload and required prior knowledge through the automation of secondary or auxiliary tasks. The introduced novel method calculates the near-optimal Cartesian end-effector pose in terms of visual feedback quality for the attached eye-to-hand camera with motion constraints in consideration. The effectiveness is demonstrated by conducting user studies of drawing reference shapes using the implemented robot avatar compared to stationary and teleoperated camera pose conditions. Our results demonstrate that the proposed control framework offers improved visual feedback quality and drawing performance.
Paper Structure (22 sections, 3 equations, 8 figures, 3 algorithms)

This paper contains 22 sections, 3 equations, 8 figures, 3 algorithms.

Table of Contents

  1. Introduction
  2. Related Work
  3. Drawing Robot Avatar
  4. Camera Viewpoint Automation
  5. Drawing Robot Avatar
  6. Hardware Setup
  7. Drawing Process
  8. Calibration Phase
  9. Teleoperation Phase
  10. Control Framework
  11. Direct Cartesian Space Teleoperation Control
  12. Unified Force and Impedance Controller
  13. Autonomous Cartesian Pose Generation
  14. User Interface
  15. Experiments
  16. ...and 7 more sections

Figures (8)

  • Figure 1: Overview of the hardware setup.
  • Figure 2: Control framework of the proposed drawing robot avatar. (Dotted line arrows are only used in experiments as the keyboard control condition)
  • Figure 3: Reference frames and spatial transform notations
  • Figure 4: Transformation from digital tablet pose to drawing robot pose
  • Figure 5: Left: visual feedback. Right: Intersection detection results
  • ...and 3 more figures