Lightbody, Peter and Hanheide, Marc and Krajnik, Tomas (2017) A versatile high-performance visual fiducial marker detection system with scalable identity encoding. In: 32nd ACM Symposium on Applied Computing, 3-7 April 2017, Marrakech, Morocco.
4d0bd9e8a3b3b5ad6ca2d56c1438fbbc.pdf - Whole Document
|Item Type:||Conference or Workshop contribution (Paper)|
|Item Status:||Live Archive|
Fiducial markers have a wide field of applications in robotics, ranging from external localisation of single robots or robotic swarms, over self-localisation in marker-augmented environments, to simplifying perception by tagging objects in a robot’s surrounding. We propose a new family of circular markers allowing for a computationally efficient detection, identification and full 3D position estimation. A key concept of our system is the separation of the detection and identification steps, where the first step is based on a computationally efficient circular marker detection, and the identification step is based on an open-ended ‘Necklace code’, which allows for a theoretically infinite number of individually identifiable markers. The experimental evaluation of the system on a real robot indicates that while the proposed algorithm achieves similar accuracy to other state-of-the-art methods, it is faster by two orders of magnitude and it can detect markers from longer distances.
|Keywords:||Swarm Robotics, Computer Vision, Fiducial Markers, bmjdoi|
|Subjects:||G Mathematical and Computer Sciences > G400 Computer Science|
H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G740 Computer Vision
|Divisions:||College of Science > School of Computer Science|
|Deposited On:||25 Jan 2017 23:58|
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