Localization in Dynamic Planar Environments Using Few Distance Measurements

TL;DR

This paper introduces a robust method for localizing sensors in dynamic 2D environments using minimal distance measurements, with proven guarantees and demonstrated effectiveness in simulations.

Contribution

The paper proposes a novel localization approach that works with few measurements and accounts for unknown dynamic obstacles, providing theoretical guarantees and practical validation.

Findings

Method achieves accurate localization with limited measurements.

Robustness under varying obstacle densities demonstrated.

Open source implementation available for testing and further research.

Abstract

We present a method for determining the unknown location of a sensor placed in a known 2D environment in the presence of unknown dynamic obstacles, using only few distance measurements. We present guarantees on the quality of the localization, which are robust under mild assumptions on the density of the unknown/dynamic obstacles in the known environment. We demonstrate the effectiveness of our method in simulated experiments for different environments and varying dynamic-obstacle density. Our open source software is available at https://github.com/TAU-CGL/vb-fdml2-public.