This study demonstrates that the use of augmented reality interfaces, designed based on a theoretically driven human-centered framework, can significantly improve task performance. The domain of unmanned ground vehicle landmine/unexploded ordnance detection and disposal was selected because it is a real-world example of a complex human-robot interaction task. Participants in this study were assigned to one of seven experimental conditions. A new method (the augmented multisensory interface design, or AMID, method) was used to identify two unisensory and one multisensory performance-enhancing augmented reality (AR) interface solutions, along with three less appropriate interface solutions. All participants were trained in the operation of the AR devices they were assigned and also in telerobotic landmine detection operations. After completing the training, participants were given the task of clearing a minefield. Results show that participants in the AMID-compliant solution groups significantly outperformed the control group and their non-AMID-compliant group counterparts in terms of the numbers of landmines correctly identified. The AMID-compliant multisensory condition was found to result in significantly increased landmine detection, increased sensitivity, and decreased task time.
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