XR pen improves robot control speed and precision in home tasks
Comparative Evaluation of an XR Pen-based Control Interface for Semi-Autonomous Mobile Robot Navigation in Service Environments
RoboticsHuman-Computer Interaction
Summary
Controlling robots at home can be tricky because they don’t work well on their own and controlling them is often hard for beginners. The authors tested a new way to guide a robot using an augmented reality pen that lets a user point and drag arrows to tell the robot where to go and how to face. They compared this pen to other XR controllers, hand gestures, and a computer method in a home-like setting. The pen made picking tasks faster and more accurate, while the XR controllers felt easiest to use, though some technical issues with the pen remain.
What this means in practice
- •For robotics developers: Use XR pen interfaces to speed up and improve precision in semi-autonomous robot navigation in home settings.
- •For augmented reality designers: Incorporate XR pen controls into AR platforms to offer novice users more intuitive robot command methods in service environments.
Authors
Alicia Torc, Carl Tornberg, Eric Piette, Renaud Ronsse, Benoit Macq, Gustavo Alfonso Garcia Ricardez, Lotfi El Hafi, Tadahiro Taniguchi
Abstract
Service robots remain difficult to deploy in domestic environments, partly because fully autonomous operation is not yet reliable in unpredictable surroundings, and partly because conventional control methods remain inaccessible to novice users. Extended Reality (XR) enables operators to visualize robot information overlaid onto the real world and to interact with augmented elements. Yet, common XR control methods, such as motion controllers and hand gestures, are still perceived as unintuitive. This paper presents a control interface that uses a commercial XR pen to command a semi-autonomous mobile robot in Augmented Reality (AR): the operator points at a position in the room, selects it, and drags an augmented arrow to set the desired orientation of the robot at this destination. Two additional interfaces, based on the XR motion controllers and hand gestures, were developed within the same framework. To assess the performance and users' perception of these interfaces, and of the XR pen in particular, a study with 10 participants compared four control methods, i.e., the XR pen, the XR motion controllers, hand gestures, and a computer-based baseline RViz, in navigation tasks performed in a home-like environment. Results show that the XR pen significantly outperforms the other methods in task selection time with the most consistent selections, and that the XR motion controllers obtain the best perceived workload and usability scores, ahead of the computer-based baseline, supporting XR-based control as an intuitive alternative for novice users. However, technical limitations in the integration of the recently released XR pen currently hold back its user experience.