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MRNaB: Mixed Reality-based Robot Navigation Interface using Optical-see-through MR-beacons

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arxiv 2403.19310 v2 pith:UQS4RPZM submitted 2024-03-28 cs.RO

classification cs.RO
keywords navigationmr-beaconsmrnabrobotinformationmixedvisualizationinterface
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Recent advancements in robotics have led to the development of numerous interfaces to enhance the intuitiveness of robot navigation. However, the reliance on traditional 2D displays imposes limitations on the simultaneous visualization of information. Mixed Reality (MR) technology addresses this issue by enhancing the dimensionality of information visualization, allowing users to perceive multiple pieces of information concurrently. This paper proposes the Mixed Reality-based Robot Navigation Interface using an Optical-see-through MR-beacons (MRNaB), a novel approach that uses MR-beacons created with an ``air tap'', situated in the real world. This beacon is persistent, enabling multi-destination visualization and functioning as a signal transmitter for robot navigation, eliminating the need for repeated navigation inputs. Our system is mainly constructed into four primary functions: ``Add'', ``Move'', ``Delete'', and ``Select''. These allow for the addition of MR-beacons, location movement, its deletion, and the selection of MR-beacons for navigation purposes, respectively. To validate the effectiveness, we conducted comprehensive experiments comparing MRNaB with traditional 2D navigation systems. The results show significant improvements in user performance, both objectively and subjectively, confirming that the MRNaB enhances navigation efficiency and user experience. For additional material, please check: https://mertcookimg.github.io/mrnab

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Cited by 1 Pith paper

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  1. Remote Life Support Robot Interface System for Global Task Planning and Local Action Expansion Using Foundation Models

    cs.RO 2024-11 conditional novelty 6.0 of 10

    A remote life-support robot interface uses @template variables in language instructions, letting the robot collect on-site information and query the user to expand uncertain task details.

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