Un enfoque basado en E2ED para la navegación y localización de robots personalizados

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 approximate the real cases of application of a robot. This is why, in parallel to research, they are also important in specialized robotics training processes. However, access to robotic platforms and laboratories is often complex and costly, with high demands on time and resources, especially 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 to work with navigation algorithms, in localization, mapping and path planning tasks. This article shows the integration of ROS into the ARMOS TurtleBot project and the design of several ROS-based subsystems to improve interaction in the development of service robot tasks. The source code of the project is available to the research community).