The Newton’s Polynomials Interpolation Based-Error Correction Method for Low-Cost Dive Altitude Sensor in Remotely Operated Underwater Vehicle (ROV)

Abstract

Indonesia is the one of the countries with the largest of sea area. However, the water surveillance categorized as minimum. The human resource and the low level of infrastructure are the causal of the minimum level of water surveillance. The human involvement of water surveillance has many weaknesses, such as weak against the change of the nature condition, limitation in reaching location, weak against water turbidity levels and water pollution. The utilization of ROV (Remotely Operated Underwater Vehicle) could be a solution in water surveillance problem. The development of ROV still not significant in Indonesia. The development costs are also a problem in development of ROV. Many researcher using USBL (Ultra Short Base Line) sensor to sense the depth of the ROV. However, the cost of this sensor is relatively expensive. The usage of low-cost pressure sensor could be a solution to replace the USBL sensor. The low-cost pressure sensor has a significant deviation. The implementation of Newton’s polynomials interpolation algorithm has been used to decreased the deviation level of the sensors. The result shows the algorithm has succeeded to decreased the deviation level of the pressure sensor significantly. The default sensor has significant MSE value of 42956.2. The Newton interpolation algorithm has been succeeded to reducing the MSE value to 17.82. The result of this research is expected to reduce the cost of the ROVs development especially for sensors cost.

Pengujian Performa 2 Degree of Freedom Underwater Remotely Operated Vehicle (Rov

“…ROV biasa digunakan untuk membantu penyelam atau memperluas kemampuan manusia untuk menjangkau laut dalam dimana para penyelam sulit bekerja secara aman dan efektif (Gandha & Nurcipto, 2019). Biasanya ROV digunakan untuk melakukan beberapa pekerjaan yaitu infeksi, manipulasi, instalasi dan pemeliharaan peralatan bawah air dan survei bawah laut (Sivcev et al, 2016).…”