Abstract: Simultaneous mapping and localization or SLAM is a basic strategy used with robots and autonomous vehicles to identify unknown environments. It is of great attention in robotics due to its importance in the development of motion planning schemes in unknown and dynamic environments, which are close to the real cases of application of a robot. This is why, in parallel with research, they are also important in specialized training processes in robotics. However, access to robotic platforms and laboratories is often complex and costly, with high demands on time and resources, particularly for small research centers. A more efficient and affordable approach to working with autonomous algorithms and motion planning schemes is often the use of the ROS-Gazebo simulator, which allows high integration with customized non-commercial robots, and the possibility of an end-to-end design (E2ED) solution. This research addresses this approach as a training and research strategy with our ARMOS TurtleBot robotic platform, creating an environment for working with navigation algorithms, in localization, mapping, and path planning tasks. This paper shows the integration of ROS into the ARMOS TurtleBot project, and the design of several subsystems based on ROS to improve the interaction in the development of service robot tasks. The project’s source code is available to the research community.

Andres Moreno, Daniel Paez and Fredy Martinez, “An E2ED-based Approach to Custom Robot Navigation and Localization” International Journal of Advanced Computer Science and Applications(IJACSA), 13(6), 2022. http://dx.doi.org/10.14569/IJACSA.2022.01306107

@article{Moreno2022,
title = {An E2ED-based Approach to Custom Robot Navigation and Localization},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.01306107},
url = {http://dx.doi.org/10.14569/IJACSA.2022.01306107},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {6},
author = {Andres Moreno and Daniel Paez and Fredy Martinez}
}