Autonomous and Teleoperation Control of a Drawing Robot Avatar

TL;DR

This paper presents a novel control framework for a drawing robot avatar that enhances telepresence drawing quality by optimizing camera pose and reducing user workload, validated through user studies.

Contribution

Introduces a new control method that calculates optimal camera poses considering visual feedback and motion constraints for improved telepresence drawing.

Findings

Enhanced visual feedback quality in telepresence drawing

Improved drawing accuracy and user experience

Validated effectiveness through user studies

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.