Dynamic Local Ball Tracking in Middle Size League Robot Soccer ERSOW based on Kaiman Filter

Abstract

The Robot Soccer uses the vision system to look for the ball continuously. The quality of vision object detection is the main factor that considered by the robot. Beside the quality, the performance of the detection process also affects the robot performance. The object detection is the heaviest process in entire ERSOW’s robot process. In this paper, we addressed the ways optimizing the vision object detection process that enhanced by the tracking method using Kaiman Filter. The Kaiman filter is also widely used for robotic purposes. The object has been equipped with a local ROI around them to limit the scanning on the entire frame when detection method is running. The local ROI will reduce the computation process and keeping the process in the sufficient resources that processor can handle. The Kaiman filter will predicted the object position and the direction of the object by considered the previous position and the times was taken. The Kaiman filter will lock the object and will follow the object without using detection feature anymore. From the results of tests conducted, the predicted value in several position has showed promising result. The average error on x-axis is 1.425 pixels and in y-axis 1.7226 pixels. This system can also reduce the average computation time from 31.67 Ms into 20.4 Ms. This research is expected to overcome the overwhelmed of the ERSOW’s computation and increased the performance of the robot