OSLo: Optical Sensor Localization through Mesh Networked Cameras

Abstract

Accurate indoor positioning remains an open research question. Existing solutions are either expensive, short-range, or inaccurate. A new approach is therefore required to cost-effectively and accurately support localization in large indoor environments. We tackle this problem by introducing a practical optical localization scheme, called OSLo, that cost-effectively scales to support large buildings. OSLo uses a meshed network of low-cost cameras as localization anchors and smart LEDs as tags, which transmit their IDs and context sensor data over the meshed cameras using optical communication. OSLo is capable of localizing dense deployments of tags with an accuracy of under 1 meter at a distance of 35 meters from the localization anchor. Furthermore, smart LED tags can be manufactured for less than $1. We systematically evaluate the performance of OSLo in the context of a real-world car localization use-case at Ford Motor Company in Germany and demonstrate promising results in terms of detection distance, and localization accuracy.