Abstract
3D modeling is a reconstruction technique used to create a 3D digital representation of real objects with varying difficulty. In robotics field, the modeling approach is often used for prototyping 3D robot models and designing virtual environments. But since 3D modeling requires essential skills and knowledge, modeling tools are hard to understand for beginners and therefore do not allow creating complex models rapidly. This paper presents a maze generation tool LIRS-MazeGen, which is an extension for the Blender modeling toolset. The extension is written in Python language and provides graphical user interface for creating 3D maze-like environments with varying difficulty in a quick manner. The tool allows creating four types of models: a regular maze, a bounded maze, an office type environment, and a warehouse environment. The output 3D models are saved into Gazebo world files and could be further easily loaded into Gazebo simulator. The generated mazes were validated using Hector SLAM and GMapping navigation algorithms with three types of mobile robots: Servosila Engineer, Husky, and TurtleBot3. The virtual tests demonstrated an acceptable level or real-time factor (RTF) that allows to use the generated Gazebo worlds in a comfortable for a user manner.
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The reported study was funded by the Russian Science Foundation (RSF) and the Cabinet of Ministers of the Republic of Tatarstan according to the research project No. 22-21-20033.
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Iskhakova, A., Abbyasov, B., Mironchuk, T., Tsoy, T., Svinin, M., Magid, E. (2023). LIRS-MazeGen: An Easy-to-Use Blender Extension for Modeling Maze-Like Environments for Gazebo Simulator. In: Ronzhin, A., Pshikhopov, V. (eds) Frontiers in Robotics and Electromechanics. Smart Innovation, Systems and Technologies, vol 329. Springer, Singapore. https://doi.org/10.1007/978-981-19-7685-8_10
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