Implementation of LiDAR Sensor for Mobile Robot Delivery Based on Robot Operating System

Authors

  • Fiqri Ahmad Agung Politeknik Negeri Padang
  • Herizon herizon Politeknik Negeri Padang
  • Era Madona Politeknik Negeri Padang
  • Muhammad Rohfadli Politeknik Negeri Padang
  • Ja'far Ja'far Warsaw University of Technology

Keywords:

Navigation System, RPLIDAR A1M8, Mobile Robot Delivery, ROS, SLAM

Abstract

Recent research has focused on the development of mobile delivery robots as part of the rapidly evolving autonomous technology. The main focus is on creating mobile robots capable of efficiently delivering goods without human intervention. This involves designing systems, core technologies, and overcoming various challenges. The navigation system of the delivery robot is enhanced by the use of LIDAR (Light Detection and Ranging) sensors. One of the sensors used is the RPLIDAR A1M8 which is capable of detecting nearby objects with a distance reading of 360°. Trials were conducted to evaluate the robot's navigation performance with a load variation of 0 kg to 20 kg. The test results show that RPLIDAR A1M8 can read distances up to 1200 cm with an error rate of about 3.15%, and a minimum distance of 15 cm with an error of 1.45%. The durability of this sensor reading is well maintained, with a presentation error of only 0.4%. Mapping trials in the room produced an average error of 18.57% without tracking, and 5.02% with tracking. The weight of the load carried by the robot affects the speed and travel time. The heavier the load, the robot speed decreases from 0.264 m/s at 0 kg load to 0.127 m/s at 20 kg load. Likewise, the travel time increases with the weight of the load, from 7.6 seconds to 15.6 seconds.

References

D. Hutabarat, M. Rivai, D. Purwanto, and H. Hutomo, “Lidar-based obstacle avoidance for the autonomous mobile robot,” Proc. 2019 Int. Conf. Inf. Commun. Technol. Syst. ICTS 2019, pp. 197–202, 2019, doi: 10.1109/ICTS.2019.8850952.

R. . P. Maulana I., A. Rusdinar, “Lidar Aplication for Mapping and Navigating on Clossed Environtment,” e-Proceeding Eng., vol. 5, pp. 1–8, 2018.

& S. S. Z. L. , S. M. I., “Perancangan Dan Implementasi Mapping System Untuk Navigasi Roner ( Robot Cleaner ),” E-Proceeding Appl. Sci., pp. 2092–2101, 2018.

M. Rohfadli, “2021 5 th International Conference on Electrical , Telecommunication and Computer Engineering Gas Leak Inspection System Using Mobile Robot Equipped With LIDAR,” 2021.

D. Ghorpade, A. D. Thakare, and S. Doiphode, “Obstacle Detection and Avoidance Algorithm for Autonomous Mobile Robot using 2D LiDAR,” 2017 Int. Conf. Comput. Commun. Control Autom. ICCUBEA 2017, pp. 1–6, 2017, doi: 10.1109/ICCUBEA.2017.8463846.

Z. Liu, “Implementation o f SLAM and path planning for mobile robots under ROS framework,” no. Icsp, 2021.

M. S. and K. M. R. E., “THE IMPLEMENTATION OF HECTOR SLAM ON THE EARTHQUAKE VICTIMS FINDER ROBOT”.

K. Makita, D. Brscic, and T. Kanda, “Recognition of Human Characteristics Using Multiple Mobile Robots with 3D LiDARs,” 2021 IEEE/SICE Int. Symp. Syst. Integr. SII 2021, pp. 650–655, 2021, doi: 10.1109/IEEECONF49454.2021.9382640.

S. Nagla, “2D Hector SLAM of Indoor Mobile Robot using 2D Lidar,” ICPECTS 2020 - IEEE 2nd Int. Conf. Power, Energy, Control Transm. Syst. Proc., pp. 18–21, 2020, doi: 10.1109/ICPECTS49113.2020.9336995.

Q. M., “ROS: an open-source Robot Operating System. In Open-source software,” ICRA, 2009.

Z. Ma, L. Zhu, P. Wang, and Y. Zhao, “ROS-Based Multi-Robot System Simulator,” pp. 4228–4232, 2019.

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Published

2023-12-31

How to Cite

Ahmad Agung, F., herizon, H., Madona, E. ., Rohfadli, M., & Ja'far, J. (2023). Implementation of LiDAR Sensor for Mobile Robot Delivery Based on Robot Operating System. JECCOM: International Journal of Electronics Engineering and Applied Science, 1(2), 66–78. Retrieved from https://elektro1.pnp.ac.id/jeccom1/index.php/ijeeas/article/view/15