Control and Navigation of Differential Drive Mobile Robot with PID and Hector SLAM: Simulation and Implementation

Authors

  • Fahmizal Fahmizal Department of Electrical Engineering and Informatics, Vocational College, Universitas Gadjah Mada
  • Matthew Sebastian Pratikno Department of Electrical Engineering and Informatics, Vocational College, Universitas Gadjah Mada
  • Hidayat Nur Isnianto Department of Electrical Engineering and Informatics, Vocational College, Universitas Gadjah Mada
  • Afrizal Mayub Graduate School of Science Education, Universitas Bengkulu
  • Hari Maghfiroh Department of Electrical Engineering, Universitas Sebelas Maret
  • Pinto Anugrah School of Electrical Engineering and Computer Science, University of Queensland, Brisbane, Australia

DOI:

https://doi.org/10.26555/jiteki.v10i3.29428

Keywords:

Mobile robot, SLAM, Path planning, Navigation, ROS

Abstract

Navigation technology is essential in fields like transportation and logistics, where precise mapping and localization are critical. Simultaneous Localization and Mapping (SLAM) technologies, such as Hector SLAM, enable robots to map environments by detecting and predicting object locations using sensors like LiDAR. Unlike other SLAM methods, Hector SLAM operates without odometry, relying solely on LiDAR data to produce accurate maps. This study investigates the application of Hector SLAM in a differential drive mobile robot controlled via the Robot Operating System (ROS), with PID control managing the motor speeds. The research contribution is the integration of Hector SLAM with PID control to enhance mapping accuracy in environments without odometry data. The method involves testing the robot's mapping performance in an indoor environment, focusing on the impact of varying linear and angular velocities on the quality of the generated maps. The PID control was tuned to ensure stable speed values for the robot's differential drive motors. Results show that Hector SLAM, when combined with well-tuned PID control, generates highly accurate maps that closely match the actual environment dimensions, with minimal errors. Specifically, the mapping error was found to be within 0.10 meters, validating the effectiveness of this approach in non-odometric systems. In conclusion, the study demonstrates that Hector SLAM, supported by PID-controlled motor stability, is an effective solution for mapping in differential drive mobile robots, particularly in scenarios where odometry is unavailable.

Downloads

Published

2024-09-16

How to Cite

[1]
F. Fahmizal, M. S. Pratikno, H. N. Isnianto, A. Mayub, H. Maghfiroh, and P. Anugrah, “Control and Navigation of Differential Drive Mobile Robot with PID and Hector SLAM: Simulation and Implementation”, J. Ilm. Tek. Elektro Komput. Dan Inform, vol. 10, no. 3, pp. 594–607, Sep. 2024.

Issue

Vol. 10 No. 3 (2024): September

Section

Articles

License

Copyright (c) 2024 Fahmizal Fahmizal, Matthew Sebastian Pratikno, Hidayat Nur Isnianto, Afrizal Mayub, Hari Maghfiroh

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors who publish with JITEKI agree to the following terms:

  1. Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.

Lisensi Creative Commons

This work is licensed under a Creative Commons Attribution 4.0 International License

Most read articles by the same author(s)