AR-Based Teleoperation of an Omnidirectional Mobile Robot for UV-C Disinfection
The COVID-19 pandemic highlighted the need for effective disinfection strategies in order to minimize human exposure and reduce the risk of contagion in indoor environments. Ultraviolet-C (UV-C) irradiation has proven to be an effective solution for inactivating a wide range of pathogens. However, traditional fixed UV-C systems suffer from limited coverage and lack operational flexibility. To address these limitations, this paper proposes an augmented reality (AR)-based teleoperation framework for an omnidirectional mobile robot equipped with a UV-C disinfection light. Unlike traditional toolchain integrations, our framework synergizes immersive spatial visualization of a reconstructed environment, operator-guided waypoint-based remote navigation, and real-time interaction with the disinfection payload in a single operational workflow. The system is implemented using a ROSMASTER X3 Plus robotic platform, which generates a three-dimensional representation of the environment through visual simultaneous localization and mapping using RTAB-Map. The result is a 3D map that is imported into the Unity game engine and deployed to a Meta Quest 3 head-mounted display, enabling immersive visualization and interaction. Communication between the AR interface and the robotic system is achieved via the ROS-TCP-Connection, allowing real-time data exchange and remote robot control. Through the AR interface, the operator can navigate the robot within the scanned environment and activate the UV-C light. Experimental validation conducted in a classroom demonstrates the feasibility of the proposed approach and shows measurable reductions in surface microbial load. These results indicate that our system-level integration of AR-assisted teleoperation with mobile UV-C robotics represents a feasible proof-of-concept for flexible, operator-guided disinfection of indoor spaces.
Authors
- Israel Soto-Marrufo
- Alma Rodriguez-Ramirez (ORCID: https://orcid.org/0000-0002-9854-1387)
- Beatriz Alvarado Robles
- Diana Ortiz-Muñoz (ORCID: https://orcid.org/0000-0001-7071-5990)
- Andres De La Rosa-Garcia
- David Luviano-Cruz
- Victor Manuel Alonso-Mendoza
- Francesco Garcia-Luna
Institutions
- Universidad Autónoma de Ciudad Juárez (MX)
Publication Details
- Journal
- Robotics
- Published
- 2026-05-01
- DOI
- https://doi.org/10.3390/robotics15050094
- Primary Topic
- Robotics and Sensor-Based Localization
- Type
- article
- Field-Weighted Citation Impact
- 0.00