The emerging simultaneous localizing and mapping (SLAM) based tracking technique allows the mobile AR device spatial awareness of the physical world. Still, smart things are not fully supported with the spatial awareness in AR. Therefore, we present Scenariot, a method that enables instant discovery and localization of the surrounding smart things while also spatially registering them with a SLAM based mobile AR system. By exploiting the spatial relationships between mobile AR systems and smart things, Scenariot fosters in-situ interactions with connected devices. We embed Ultra-Wide Band (UWB) RF units into the AR device and the controllers of the smart things, which allows for measuring the distances between them. With a one-time initial calibration, users localize multiple IoT devices and map them within the AR scenes. Through a series of experiments and evaluations, we validate the localization accuracy as well as the performance of the enabled spatial aware interactions. Further, we demonstrate various use cases through Scenariot.
Ke Huo, Yuanzhi Cao, Sang Ho Yoon, Zhuangying Xu, Guiming Chen, Karthik Ramani
Scenariot: Spatially Mapping Smart Things Within Augmented Reality Scenes
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018, April 21–26, 2018, Montreal, QC, Canada