Research on Position Estimation of Curling Stones Around House by Mobile Robot

Abstract

In sports and technology, the fusion of artificial intelligence and image processing has introduced innovative avenues to elevate performance and precision in conventional sports. Curling, distinguished for its strategic complexities, revolves around the trajectory and positioning of its uniquely contoured stones. The accurate determination of stone positions assumes a pivotal role in devising strategies and attaining favorable throwing outcomes. This study presents a foundational methodology that aims to position estimation of curling stones around house by mobile robot. The approach seamlessly integrates two key components: image recognition and interpolation, leveraging the Support Vector Machine (SVM) algorithm for stone identification, complemented by sophisticated image interpolation techniques to achieve unparalleled accuracy. We conducted trials of our method using real image data collected from curling field. Leveraging SVM enabled effective stone recognition, followed by the application of image interpolation techniques to precisely estimate stone positions, based on their shapes and relative placements. Experimental results on real data have shown the impressive performance of the proposed method. The combination of SVM and interpolated image processing has greatly improved the ability to estimate the position of the stones in the sport of curling. This method not only yields accurate results, but also opens the door for future optimization and development.