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The paper introduces VirTooS, a toolkit that integrates ROS 2 and the Unity game engine to facilitate fleet management tasks for Autonomous Mobile Robots (AMRs) in a mixed-reality environment. This toolkit enables users to create and customize virtual scenarios for realistic simulations, utilizing both virtual and real sensors for effective mapping and navigation. Key results demonstrate the effectiveness of VirTooS in conducting distributed robotics experiments, particularly in task assignment problems, showcasing seamless interaction between real and virtual robots.
VirTooS enables realistic mixed-reality simulations that enhance fleet management for Autonomous Mobile Robots, bridging the gap between virtual and real-world robotics.
In this paper, we present VirTooS, a Python/C# toolkit designed to implement fleet-management tasks on teams of Autonomous Mobile Robots (AMRs). VirTooS leverages the Robot Operating System (ROS) 2 and Unity game engine to provide realistic, scalable virtual experiments in a mixed-reality environment. The toolbox allows users to easily generate and customize virtual scenarios for realistic simulations. Virtual and real sensors as, e.g., LiDARs, can be exploited to map and safely navigate in the mixed-reality environment. To enable distributed robotics experiments, we propose a set of tailored routines leveraging the ChoiRbot framework. As a motivating example, we show a set of experiments for task assignment problems in a virtual environment, allowing seamless interaction among real and virtual robots. Moreover, the package comes with a containerized suite to easily deploy it on different machines. The source code will be made publicly available on GitHub.
