Main Article Content


One of the causes of accidents on trains to date has been caused by damage of railways such as cracked rails, broken rails and other rail defects. Currently, the inspection of the railway line is still carried out manually by the railway inspection officer or Petugas Penilik Jalan Rel (PPJ). However, there is a prototype Autonomous Railways Monitoring Robot (ARMR) which is a prototype inspection robot that can perform rail line checks automatically and be monitored remotely to detect any faults on the railway. The ARMR prototype detects faults as well as locations that are subsequently delivered to users by utilizing some Internet of Things (IoT) features. Faults detected by ARMR prototypes are faults as rail damage. But, the ARMR prototype is unable to distinguish a fault and rail connection. This final task aims to improve armr prototype capabilities to produce information in the form of depth and width of faults, and to distinguish faults and rail connections. The VL6180X sensor is a laser- based distance sensor used as a depth detector for rail faults and rail connections. The Incremental Encoder is enabled to measure the width of the rail fault. The result of ten experiments at 20 cm/s, the ARMR prototype was able to produce 78 mm fault depth size information with an error value of 1,67%, produce 5 mm wide fault width information with an error value of 2,48 % and be able to distinguish faults and connections with 72 % accuracy for the comparison of the distance between the ARMR prototype and the distance shown on google maps.

Article Details

How to Cite
Rokhim, I., Nabila, D., & Sunarya, A. (2021). Improvement of autonomous railway monitoring robot prototype as fault detection on railway. INVOTEK: Jurnal Inovasi Vokasional Dan Teknologi, 21(3), 189-202.


  1. [1] Kementrian perhubungan, “Menteri perhubungan republik indonesia,” Peraturan. Menteri Perhub. Republik Indones. Nomor Pm 115 Tahun 2018, pp. 1–8, 2018.
  2. [2] Siti Fatimah “Implementasi Prototype Autonomous Railway Monitoring Robot sebagai Pendeteksi Patahan pada Rel Kereta Api”, Tugas Akhir D IV Politeknik Manufaktur Bandung, 2019.
  3. [3] Rohmat Santoso, “Autonomous Railways Monitoring Robot Berbasis Raspberry Pi Sebagai Prototipe Robot Alat Bantu Petugas Inspeksi Rel Kereta Api”, T. Elektronika, F. Teknik, U. N. Yogyakarta, 2019.
  4. [4] Daryono Restu Wahono, “Mendeteksi Kondisi Rel Putus Menggunakan Akselerometer dan Kamera Visi”, Puslit KIM-LIPI Serpong-Tanggerang, 2013.
  5. [5] R. Sireesha, A. K. B, G. Mallikarjunaiah, and B. K. B, “Broken Rail Detection System using RF Technology,” vol. 2, no. 4, pp. 11–15, 2015, doi: 10.1210/endo.137.10.8828507.
  6. [6] R. Nicolau, “Omnidirectional scanner using a time of flight sensor by,” no. February, 2018.
  7. [7] P. Dana and B. Pemerintah, “Laporan Akhir Laporan Akhir,” pp. 78–79, 2019.
  8. [8] ST Microelectronics, “Proximity and ambient light sensing (ALS) module VL6180X (Datasheet),” VL6180X datasheet, no. June, pp. 1–87, 2016.
  9. [9] A. Falamarzi, S. Moridpour and M. Nazem, ”A Review on Existing Sensors and Devices for Inspecting Railway Infrastructure”, Jurnal Kejuruteraan 31(1), 2019, pp 1-10
  10. [10] N. Mahfuz, O. A. Dhali, S. Ahmed, and M. Nigar, “Autonomous railway crack detector robot for Bangladesh: SCANOBOT,” in 5th IEEE Region 10 Humanitarian Technology Conference 2017, R10-HTC 2017, 2018, vol. 2018- Janua, pp. 524–527, doi: 10.1109/R10-HTC.2017.8289014.