We present the design, implementation, and evaluation of MiFly, a self-localization system for autonomous drones that works across indoor and outdoor environments, including low-visibility, dark, and GPS-denied settings. MiFly performs 6DoF self-localization by leveraging a single millimeter-wave (mmWave) anchor in its vicinity - even if that anchor is visually occluded. MiFly's core contribution is in its joint design of a mmWave anchor and localization algorithm. The low-power anchor features a novel dual-polarization dual-modulation architecture, which enables single-shot 3D localization. Mm Wave radars mounted on the drone perform 3D localization relative to the anchor and fuse this data with the drone's internal inertial measurement unit (IMU) to estimate its 6DoF trajectory. We implemented and evaluated MiFly on a DJI drone. We collected over 6,600 localization estimates across different trajectory patterns and demonstrate a median localization error of 7 cm and a 90thpercentile less than 15 cm, even in low-light conditions and when the anchor is fully occluded (visually) from the drone. Demo video: voutu.be/LfXfZ26tEok

This demo presents X-AR, an Augmented Reality headset that enables its user to find and retrieve hidden items. X-AR leverages battery-less 3-cent Radio Frequency IDentification (RFID) tags that are already deployed on billions of items. As a user wearing X-AR moves in an environment, the headset transmits RF signals and leverages natural human mobility to locate RFID-tagged items. X-AR then guides the user toward the desired item for retrieval. We built a real-time prototype of this system on a Microsoft Hololens 2 AR headset with a conformal antenna, software radios, and an edge server. Our demo will enable any user to wear our X-AR prototype and use it to find and retrieve hidden items in a warehouse-like setting. Demo Video: youtu.be/bdUN21ft7G0