Problem
Research questions and friction points this paper is trying to address.
Service Robots
Extended Reality (XR)
Semi-Autonomous Navigation
Control Interface
Novice Users
Comparative Evaluation of an XR Pen-based Control Interface for Semi-Autonomous Mobile Robot Navigation in Service Environments
🤖 AI Summary
This study addresses the challenges of service robot manipulation in unstructured environments and the unintuitive nature of novice interaction by proposing an augmented reality (AR) control interface for semi-autonomous mobile robots based on an XR pen. A novel interaction paradigm is introduced, enabling users to specify target poses through XR pen pointing and dragging gestures. The navigation performance and user experience of the XR pen, XR controller, hand gesture, and conventional methods are systematically compared within a domestic scenario. Experimental results demonstrate that the XR pen significantly reduces task selection time while achieving optimal consistency, whereas the XR controller performs best in terms of workload and usability. These findings provide an efficient and intuitive solution for spatial robot manipulation.
📝 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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Extended Reality (XR)
XR Pen Interface
Semi-Autonomous Navigation
Augmented Reality (AR)
Human-Robot Interaction
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