The demand for mobile robots that perform the task of autonomous transport has grown in research
institutes, such as Innovation Hub/IFAM, and the technology for their manufacture, configuration
and implementation in an industrial environment covers several, current and future, problems that
robotics proposes to solve. These problems sometimes seem easy for human beings, such as
walking, communicating and recording the environment around them through maps. Such tasks
require the integration of actuators, sensors and systems focused on odometry and creation of
cartographic records. The challenges increase when the robot in question responsible for mapping
must work in a dynamic environment, that is, where obstacles, which must be avoided, can appear,
disappear or move around the map. One framework developed aiming to achieving these
functionalities is ROS (Robot Operating System) which provides a platform for creating code, in
Python and C++, and tools to be used in robotics systems in general, with emphasis on applications
such as industrial AGVs (Automated Guided Vehicles), military UGV (Unmanned Ground
Vehicle), emergency response vehicles and space explores such as ROVER MARS 2020, and
perhaps most importantly, for sharing solutions between the most diverse types of robots. This
work details the construction of a teleoperated robot with the ability to map indoor environments
using a LiDAR (Light Detection and Ranging) sensor combined with HECTOR SLAM in the ROS
platform, as the robotic system responsible for synchronizing sensors, actuators and algorithms.
Although delivering satisfactory results, the developed robotic platform encounters difficulties in
generating odometry due to problems reading the encoder sensors and wheel slippage on smooth
terrain.
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