ORIGINAL RESEARCH article
Front. Robot. AI
Sec. Computational Intelligence in Robotics
SimNav-XR: An Extended Reality Platform for Mobile Robot Simulation Using ROS2 and Unity3D
1. Institut für Informatik, Fakultät für Naturwissenschaften und Naturwissenschaften, Universität Bern, Bern, Switzerland
2. BITS Pilani - Dubai Campus, Dubai, United Arab Emirates
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Abstract
This paper presents SimNav-XR, an extended reality platform that integrates XR technologies with modern robotics frameworks to support mobile robot simulation and development. By connecting ROS2's communication infrastructure with Unity3D's rendering and XR capabilities through the ROS-TCP-Connector package, SimNav-XR provides a practical bridge between robotics middleware and game engine environments for visualization and testing. The platform implements components for physics-based robot modeling, LiDAR and IMU sensor simulation, environmental interaction dynamics, and XR interfaces supporting both Virtual Reality (VR) and Mixed Reality (MR) modes. These capabilities create interactive environments where developers can visualize and control simulated robots through immersive interfaces using the Meta Quest 3 headset with controller-based input. Experimental evaluations using established platforms (Turtlebot3 and ROSbotXL) demonstrate the framework's capabilities across virtual testing scenarios, showing successful autonomous navigation with obstacle avoidance and simultaneous localization and mapping (SLAM). The VR mode provides fully immersive virtual environments for development and testing, while the MR mode uses passthrough cameras to overlay virtual robots onto real-world surfaces via plane detection. XR visualization techniques provide insights into robot sensor data and navigation behavior, supporting robotics development and education through accessible simulation environments.
Summary
Keywords
Autonomous navigation, Extended Reality, Mixed reality, mobile robots, robotics simulation, ROS2, Unity3D, virtual reality
Received
18 September 2025
Accepted
21 January 2026
Copyright
© 2026 Aryan, Shetty, Venkatesan and Karthikeyan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Prakash Aryan; Sujala Deepak Shetty
Disclaimer
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