Object Position Estimation based on Dual Sight Perspective Configuration

Main Article Content

Dion Setiawan
Maulana Ifdhil Hanafi
Indra Riyanto
Akhmad Musafa

Abstract

Development of the coordination system requires dataset, because the dataset could provide information around the system that can be used by the coordination system to make decisions. The capability to process and display data related positions of objects around the robots is necessary. This paper provides a method to predict an object’s position. This method is based on the idea of the Indoor Positioning System (IPS) and object position estimation with multi-camera system (i.e. stereo vision). This method needs two input data to estimate the ball position: input image, and the robot’s relative position. The approach adopts simple and easy calculation technics: trigonometry, angle rotations, and linear function. This method was tested on a ROS and Gazebo simulation platform. The experimental result shows that this configuration could estimate the object’s position with Mean Squared Error was 0.383 meters and R squared distance calibration value is 0.9932, which implies that this system worked very well at estimating an object’s position.


 

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Article Details

How to Cite
[1]
D. Setiawan, M. Hanafi, I. Riyanto, and A. Musafa, “Object Position Estimation based on Dual Sight Perspective Configuration”, INFOTEL, vol. 13, no. 2, May 2021.
Section
Electronics
Author Biographies

Dion Setiawan, Universitas Budi Luhur

First Author

Maulana Ifdhil Hanafi, Universitas Budi Luhur

Third Author

Akhmad Musafa, Universitas Budi Luhur

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