Abstract
Nowadays robot simulators have robust physics engines, high-quality graphics, and convenient interfaces, affording researchers to substitute physical systems with their simulation models in order to pre-estimate the performance of theoretical findings before applying them to real robots. This paper describes Gazebo simulation approach to simultaneous localization and mapping (SLAM) based on Robot Operating System (ROS) using PR2 robot. The ROS-based SLAM approach applies Rao-Blackwellized particle filters and laser data to locate the PR2 robot in unknown environment and build a map. The real room 3D model was obtained from camera shots and reconstructed with Autodesk 123D Catch and MeshLab software. The results demonstrate the fidelity of the simulated 3D room to the obtained from the robot laser system ROS-calculated map and the feasibility of ROS-based SLAM with a Gazebo-simulated mobile robot to its usage in camera-based 3D environment. This approach will be further extended to ROS-based robotic simulations in Gazebo with a Russian anthropomorphic robot AR-601M.
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Afanasyev, I., Sagitov, A., Magid, E. (2015). ROS-Based SLAM for a Gazebo-Simulated Mobile Robot in Image-Based 3D Model of Indoor Environment. In: Battiato, S., Blanc-Talon, J., Gallo, G., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2015. Lecture Notes in Computer Science(), vol 9386. Springer, Cham. https://doi.org/10.1007/978-3-319-25903-1_24
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DOI: https://doi.org/10.1007/978-3-319-25903-1_24
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