Implementação de algoritmo Hector Slam em veículos terrestre não tripulado em ambiente dinâmico e sem acesso a GPS.

Abstract

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.