On-line Optimal Ranging Sensor Deployment for Robotic Exploration

TL;DR

This paper introduces a self-deployable UWB infrastructure for robotic exploration, enabling dynamic placement of anchors and optimizing deployment to control positioning uncertainty, demonstrated through simulations and indoor drone experiments.

Contribution

It presents a novel genetic algorithm for optimal anchor deployment that minimizes resource use while maintaining positioning accuracy during exploration.

Findings

Maximum positioning uncertainty is kept below user threshold.

The approach effectively extends UWB infrastructure during exploration.

Simulations and experiments validate the method's efficiency.

Abstract

Navigation in an unknown environment without any preexisting positioning infrastructure has always been hard for mobile robots. This paper presents a self-deployable ultra wideband UWB infrastructure by mobile agents, that permits a dynamic placement and runtime extension of UWB anchors infrastructure while the robot explores the new environment. We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows. Moreover, we developed a genetic algorithm that minimizes the deployment of new anchors, saving energy and resources on the mobile robot and maximizing the time of the mission. Although the presented approach is general for any class of mobile system, we run simulations and experiments with indoor drones. Results demonstrate that maximum positioning uncertainty is always controlled under the user's threshold, using the Geometric Dilution of Precision (GDoP).