Indonesian Journal of Computer Science
Vol. 12 No. 1 (2023): Indonesian Journal of Computer Science Volume 12. No. 1 (2023)

Online Terrain Classification Using Neural Network for Disaster Robot Application

Muhammad Anwar Sanusi (Politeknik Elektronika Negeri Surabaya)
Bima Sena Bayu Dewantara (Politeknik Elektronika Negeri Surabaya)
Setiawardhana (Politeknik Elektronika Negeri Surabaya)
Riyanto Sigit (Politeknik Elektronika Negeri Surabaya)

Article Info

Publish Date
28 Feb 2023


A disaster robot is used for crucial rescue, observation, and exploration missions. In the case of implementing disaster robots in bad environmental situations, the robot must be equipped with appropriate sensors and good algorithms to carry out the expected movements. In this study, a neural network-based terrain classification that is applied to Raspberry using the IMU sensor as input is developed. Relatively low computational requirements can reduce the power needed to run terrain classification. By comparing data from the Accelerometer, Gyroscope, and combined Accelero-Gyro using the same neural network architecture, the tests were carried out in a not moving position, indoors, on asphalt, loose gravel, grass, and hard ground. In its implementation, the mobile robot runs over the field at a speed of about 0,5 m/s and produces predictive data every 1,12s. The prediction results for online terrain classification are above 93% for each input tested.

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Journal Info





Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering


The scope of IJCS includes general computer science, information system, information technology, artificial intelligence, big data, industrial revolution 4.0, and general ...