Robots are being created each year with the goal of integrating them into our daily lives. As such, there is an interest in research in evaluating the trust of humans toward robots. In addition, teleoperating robotic arms can be challenging for non-experts. To reduce the strain put on the user, we created TELESIM, a modular and plug-and-play framework that enables direct teleoperation of any robotic arm using a digital twin as the interface between users and the robotic system.
We evaluated our framework using a user survey with three robots and User Interface Device (UID) and recorded the user's workload and performance at completing a tower stacking task. However, an analysis of the strain on the user and their ability to trust robots was omitted. This paper addresses these omissions by presenting the additional results of our user survey of 37 participants carried out in United Kingdom. In addition, we present the results of an additional user survey, under similar conditions performed in Japan, with the goal of addressing the limitations of our previous approach, by interfacing a VR controller with a UR5e, henceforth referred to as Yellow Design.
Our experimental results show that the Yellow Design has more towers built. Additionally, the Yellow Design gives the least amount of cognitive stress, while the combination of Senseglove and UR3 provides the user with the highest physical strain and causes the user to feel more frustrated. Finally, the Japanese participants seem more trusting of robots than the British participants.
The controllers (in the black dotted line)(1) can be any system that outputs a 3D pose, while our framework is depicted in the blue dotted line. It accepts the pose given by (1) to update the 3D pose of a cube in the digital twin. The robot then calculates a path to this cube in real-time, while avoiding collision with the world (4). Finally, TELESIM can be plugged into any robotic system (6) via a ROS2 robot controller (5)\, as shown in the red dotted line.
The Steam Index VR Headset is marked as (1) on the far left, which acts as the world’s origin. The Baxter robot on the left (2) is controlled by the Steam Index controller (5). In front of it, the UR3 is on the right (3), with the Yale OpenHand T42 gripper, controlled by the Senseglove and HTC Vive tracker (4) on the left side of the brown table. Additionally, in the upper right corner (7), a view of the starting setup of the task, which consists of 3 cubes in a triangle pattern, while on the brown table, the cubes are arranged in the goal configuration (6).
85% of the participants can build at least one tower in 10 minutes using Baxter and the VR controller. However, there is a steady decline for each of the following towers, with only 5% of the users able to build 8 towers. This is in direct comparison to the UR3, with slightly less than 50% of the population failing to build one tower and 5% managing to build 4, half as many towers for Baxter.
We thank the University of Glasgow for the use of the Baxter robot and the UR3 robot. We also thank the EPSCR for funding this research. Finally we thank all the participants who took part in our experiments.
@misc{audonnet2024breakingbarriersinvestigatingnonexpert,
title={Breaking Down the Barriers: Investigating Non-Expert User Experiences in Robotic Teleoperation in UK and Japan},
author={Florent P Audonnet and Andrew Hamilton and Yakiyasu Domae and Ixchel G Ramirez-Alpizar and Gerardo Aragon-Camarasa},
year={2024},
eprint={2410.18727},
archivePrefix={arXiv},
primaryClass={cs.RO},
url={https://arxiv.org/abs/2410.18727},
}