MAPPING THE WHEEL ROBOT WORKING ENVIRONMENT WITH SLAM GMAPPING METHOD USING LIDAR SENSOR

  • Noeroes Shobie Ahfan Universitas Budi Luhur
  • Peby Wahyu Purnawan
  • Sujono Sujono
  • Akhmad Musafa
  • Indra Riyanto

Abstract

The wheeled robot used to deliver documents between rooms must be able to move according to the environmental conditions of the work area. For this reason, the robot must have knowledge of the conditions of the work environment to be passed. In this final project, the work area environment mapping on the wheeled robot is carried out. Mapping was done using the Simultaneous Localization and Mapping (SLAM) method. The equipment used in the mapping is a lidar sensor. The robot system consists of a raspberry Pi 4 which is used as the main controller of the robot. The robot has two sensors. The first sensor is a lidar sensor, which is used to detect the distance of the object in front of the robot. Then the IMU sensor is used to detect the robot's orientation and position changes. In the robot there is a motor driver which is used as a robot control signal processor to drive a DC motor. Map making is done by means of a lidar sensor reading the robot's working area environment. The lidar sensor output signal is processed using the SLAM gmapping method. In this test, to determine the environment of the robot's work area, using a laser scanner to produce a two-dimensional (2D) map, while estimating the position of the robot on the map using a particle filter. This simultaneous mapping uses the Simultaneous Localization and Mapping (SLAM) mapping algorithm based on Raspberry Pi 4. The results obtained are maps in grayscale. In addition to SLAM gmapping, this article also shows that there are one to three robot position 2D testing arenas.

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Published
2022-11-04
How to Cite
AHFAN, Noeroes Shobie et al. MAPPING THE WHEEL ROBOT WORKING ENVIRONMENT WITH SLAM GMAPPING METHOD USING LIDAR SENSOR. MAESTRO, [S.l.], v. 5, n. 2, p. 295 - 303, nov. 2022. ISSN 2655-3430. Available at: <https://jom.ft.budiluhur.ac.id/index.php/maestro/article/view/546>. Date accessed: 19 july 2024.