Real-Time Ellipse Detection for Robotics Applications

TL;DR

This paper introduces a lightweight, real-time ellipse detection algorithm tailored for robotics, capable of handling lighting variations and partial views, demonstrated on UAV landing tasks with superior accuracy.

Contribution

The paper presents a novel, resource-efficient ellipse detection method that outperforms existing techniques in real-world robotics scenarios.

Findings

Achieved an F1 score of 0.981 on over 1500 frames dataset.

Demonstrated robustness in indoor, outdoor, and simulation environments.

Enabled real-time ellipse detection on resource-limited onboard computers.

Abstract

We propose a new algorithm for real-time detection and tracking of elliptic patterns suitable for real-world robotics applications. The method fits ellipses to each contour in the image frame and rejects ellipses that do not yield a good fit. The resulting detection and tracking method is lightweight enough to be used on robots' resource-limited onboard computers, can deal with lighting variations and detect the pattern even when the view is partial. The method is tested on an example application of an autonomous UAV landing on a fast-moving vehicle to show its performance indoors, outdoors, and in simulation on a real-world robotics task. The comparison with other well-known ellipse detection methods shows that our proposed algorithm outperforms other methods with the F1 score of 0.981 on a dataset with over 1500 frames. The videos of experiments, the source codes, and the collected dataset are provided with the paper at https://theairlab.org/landing-on-vehicle .