ARLCL: Anchor-free Ranging-Likelihood-based Cooperative Localization

This *dataset (68440 files of approx. 30GB unzipped) includes all Bluetooth Low Energy (BLE) Received Signal Strength (RSS) samples used for the evaluation of the Anchor-free Ranging-Likelihood-based Cooperative Localization (ARLCL) method. Each DB file corresponds to an evaluated scenario of a unique combination of nodes/samples (i.e. reflecting different swarm deployments and measurement qualities). The maximal setting is 21 Raspberry Pis and 20 RSS measurement samples. Each DB file contains the true positions of the participating nodes, 100 resampling cases, and one exceptional case (#RSS_0#) where all samples have been used (this case has not been considered in the paper).<br> <br> The specific structure of the DB files is required by our open-sourced Cooperative Localization Optimizer (<em><strong>ARLCL-Optimizer</strong></em>), and also the <strong>Mass Spring</strong> and <strong>Maximum Likelihood - Particle Swarm Optimization</strong> implementations that we used in the paper. These are also provided openly in our repo (https://github.com/CDS-Bern/ARLCL-Optimizer).<br> <br> We encourage future cooperative localization solutions to use our provided dataset/software for comparisons or results reproduction. *The files have been compressed using 7-zip.