Enabling Relative Localization for Nanodrone Swarm Platooning

TL;DR

This paper introduces RFDrone, a wireless-based system for estimating the relative positions of nanodrones in a swarm, enabling safe indoor platooning without relying on vision or motion sensors.

Contribution

It presents a novel RF-based localization method using RFID tags and phase profiling, tailored for nanodrone swarms in challenging indoor environments.

Findings

Achieves around 0.95 accuracy in relative localization

Provides about 0.93 accuracy in swarm geometry estimation

Demonstrates effective real-world prototype implementation

Abstract

Nanodrone swarm is formulated by multiple light-weight and low-cost nanodrones to perform the tasks in very challenging environments. Therefore, it is essential to estimate the relative position of nanodrones in the swarm for accurate and safe platooning in inclement indoor environment. However, the vision and infrared sensors are constrained by the line-of-sight perception, and instrumenting extra motion sensors on drone's body is constrained by the nanodrone's form factor and energy-efficiency. This paper presents the design, implementation and evaluation of RFDrone, a system that can sense the relative position of nanodrone in the swarm using wireless signals, which can naturally identify each individual nanodrone. To do so, each light-weight nanodrone is attached with a RF sticker (i.e., called RFID tag), which will be localized by the external RFID reader in the inclement indoor environment. Instead of accurately localizing each RFID-tagged nanodrone, we propose to estimate the relative position of all the RFID-tagged nanodrones in the swarm based on the spatial-temporal phase profiling. We implement an end-to-end physical prototype of RFDrone. Our experimental results show that RFDrone can accurately estimate the relative position of nanodrones in the swarm with average relative localization accuracy of around 0.95 across x, y and z axis, and average accuracy of around 0.93 for nanodrone swarm's geometry estimation.