Object Position Estimation based on Dual Sight Perspective Configuration

Abstract

Development of the coordination system requires the dataset because the dataset could provide information around the system that the coordination system can use to make decisions. Therefore, 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 Indoor Positioning System (IPS) idea and object position estimation with the multi-camera system (i.e., stereo vision). This method needs two input data to estimate the ball position: the 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. Besides, R squared distance calibration value is 0.9932, which implies that this system worked very well at estimating an object’s position.