# Localizing Backscatters by a Single Robot With Zero Start-up Cost

## TL;DR

This paper introduces Rover, a zero-startup-cost indoor localization system that uses a robot with inertial sensors to accurately locate multiple backscatter tags without prior site knowledge.

## Contribution

Rover is the first system to localize multiple backscatter tags simultaneously without requiring prior site maps or landmarks, using joint optimization of WiFi and inertial data.

## Key findings

- Achieves 39.3 cm accuracy for robot localization
- Achieves 74.6 cm accuracy for backscatter tags
- Handles interference and real-time SLAM processing

## Abstract

Recent years have witnessed the rapid proliferation of low-power backscatter technologies that realize the ubiquitous and long-term connectivity to empower smart cities and smart homes. Localizing such low-power backscatter tags is crucial for IoT-based smart services. However, current backscatter localization systems require prior knowledge of the site, either a map or landmarks with known positions, increasing the deployment cost. To empower universal localization service, this paper presents Rover, an indoor localization system that simultaneously localizes multiple backscatter tags with zero start-up cost using a robot equipped with inertial sensors. Rover runs in a joint optimization framework, fusing WiFi-based positioning measurements with inertial measurements to simultaneously estimate the locations of both the robot and the connected tags. Our design addresses practical issues such as the interference among multiple tags and the real-time processing for solving the SLAM problem. We prototype Rover using off-the-shelf WiFi chips and customized backscatter tags. Our experiments show that Rover achieves localization accuracies of 39.3 cm for the robot and 74.6 cm for the tags.