Multi-User Augmented Reality with Infrastructure-free Collaborative Localization

TL;DR

LocAR is an infrastructure-free, real-time 6DoF localization system for multi-user AR that uses visual-inertial odometry and UWB ranging to achieve high accuracy without prior setup.

Contribution

This paper introduces LocAR, a novel infrastructure-free collaborative localization system for AR that operates without global coordinates or map sharing, enabling practical multi-user AR in dynamic environments.

Findings

Achieves median 3D error of less than 1 meter across multiple users and floors.

Operates effectively in large, complex environments without infrastructure.

Provides real-time AR visualization of team members' locations.

Abstract

Multi-user augmented reality (AR) could someday empower first responders with the ability to see team members around corners and through walls. For this vision of people tracking in dynamic environments to be practical, we need a relative localization system that is nearly instantly available across wide-areas without any existing infrastructure or manual setup. In this paper, we present LocAR, an infrastructure-free 6-degrees-of-freedom (6DoF) localization system for AR applications that uses motion estimates and range measurements between users to establish an accurate relative coordinate system. We show that not only is it possible to perform collaborative localization without infrastructure or global coordinates, but that our approach provides nearly the same level of accuracy as fixed infrastructure approaches for AR teaming applications. LocAR uses visual-inertial odometry (VIO) in conjunction with ultra-wideband (UWB) ranging radios to estimate the relative position of each device in an ad-hoc manner. The system leverages a collaborative 6DoF particle filtering formulation that operates on sporadic messages exchanged between nearby users. Unlike map or landmark sharing approaches, this allows for collaborative AR sessions even if users do not overlap the same spaces. LocAR consists of an open-source UWB firmware and reference mobile phone application that can display the location of team members in real-time using mobile AR. We evaluate LocAR across multiple buildings under a wide-variety of conditions including a contiguous 30,000 square foot region spanning multiple floors and find that it achieves median geometric error in 3D of less than 1 meter between five users freely walking across 3 floors.