Infrastructure-free Localization of Aerial Robots with Ultrawideband Sensors

TL;DR

This paper presents an onboard, infrastructure-free localization method for aerial robot swarms using ultrawideband sensors, enabling accurate position estimation without external systems or inter-robot communication.

Contribution

It introduces a dual Monte-Carlo localization framework that relies solely on onboard UWB sensors, eliminating the need for external infrastructure or explicit inter-robot communication.

Findings

High localization accuracy across various robot speeds

Superior performance over standard particle filter and EKF

Validated through simulations and outdoor experiments

Abstract

Robots in a swarm take advantage of a motion capture system or GPS sensors to obtain their global position. However, motion capture systems are environment-dependent and GPS sensors are not reliable in occluded environments. For a reliable and versatile operation in a swarm, robots must sense each other and interact locally. Motivated by this requirement, here we propose an on-board localization framework for multi-robot systems. Our framework consists of an anchor robot with three ultrawideband (UWB) sensors and a tag robot with a single UWB sensor. The anchor robot utilizes the three UWB sensors as a localization infrastructure and estimates the tag robot's location by using its on-board sensing and computational capabilities solely, without explicit inter-robot communication. We utilize a dual Monte-Carlo localization approach to capture the agile maneuvers of the tag robot with an acceptable precision. We validate the effectiveness of our algorithm with simulations and indoor and outdoor experiments on a two-drone setup. The proposed dual MCL algorithm yields highly accurate estimates for various speed profiles of the tag robot and demonstrates a superior performance over the standard particle filter and the extended Kalman Filter.