ATMAS: Assistive Teleoperation Method using Augmented Reality and Switching Control

Abstract

This paper presents an assistive teleoperation method using a combination of Augmented Reality (AR) markers and control switching between the operator and robot. This method is designed to enhance remote manipulation tasks in retail environments like convenience stores. The system integrates a novel intention recognition algorithm for predicting goals, augmented reality markers for visual guidance, and a variable autonomy framework. The system is able to adapt under goal switching, which otherwise fails for existing methods. A user study with 7 participants compared our method against two other teleoperation methods in terms of objective and subjective metrics. Results showed that our method significantly reduced collisions during task execution. The study provides insights into the strengths and limitations of augmented reality assistance and variable autonomy in teleoperation, laying groundwork for future research in enhancing human-robot collaboration for retail automation tasks.