Multi-Perspective Ar Interaction Through Robot Viewpoint Control
Abstract
Industrial environments increasingly deploy robots, creating a need for intuitive spatial interaction. Augmented Reality (AR) supports this, but can become difficult to use in large or occluded spaces where users lack direct views and fixed cameras are impractical. We address this by using a mobile robot as a live, repositionable viewpoint for AR workspace editing. We present a multi-perspective AR system and compare joystick and touch-based gesture control of a mobile robot viewpoint during AR object manipulation. In two user studies, we isolated task-dependent effects (navigation-only vs. manipulation-supported) and evaluated performance in realistic editing tasks. Results indicate that mobile robot viewpoints can support AR interaction in inaccessible areas without fixed camera infrastructure. Joystick control showed advantages for navigation-only viewpoint repositioning, whereas no clear performance difference emerged when viewpoint control supported a touch-based manipulation task. These findings indicate a task-dependent trade-off between control efficiency and interaction integration. We discuss design implications for task-dependent viewpoint control for AR interaction without fixed infrastructure.