Abstract
Simulation has proven to be a highly effective tool for validating autonomous systems while lowering cost and increasing safety. Currently, several dedicated simulation environments exist, but they are limited in terms of environment size, visual quality, and feature sets. As a result, many researchers have begun to consider repurposing game engines as simulators to take advantage of their greater flexibility, scalability, and graphical fidelity. This study investigates a robotics simulation environment based on the Unity3D game engine and Robot Operating System (ROS) middleware, collectively referred to as ROS-Unity3D, and compares it to the popular ROS-Gazebo robotics simulation environment. They are compared in terms of their architecture, environment creation process, resource usage, and accuracy while simulating an autonomous ground robot in real-time. Overall, with its variety of supported file types and powerful scripting interface for creating custom functionality, ROS-Unity3D is found to be a viable alternative to ROS-Gazebo. Test results indicate that ROS-Unity3D scales better to larger environments, has higher shadow quality, achieves the same or better visual-based SLAM performance, and is more capable of real-time LiDAR simulation than ROS-Gazebo. As for its advantages over ROS-Unity3D, ROS-Gazebo has a more streamlined interface between ROS and Gazebo, has more existing sensor plugins, and is more computer resource efficient for simulating small environments.
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Source code and experimental data from the current study is available from the corresponding author on reasonable request.
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Jonathan Platt. The first draft of the manuscript was written by Jonathan Platt and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Platt, J., Ricks, K. Comparative Analysis of ROS-Unity3D and ROS-Gazebo for Mobile Ground Robot Simulation. J Intell Robot Syst 106, 80 (2022). https://doi.org/10.1007/s10846-022-01766-2
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DOI: https://doi.org/10.1007/s10846-022-01766-2