Towards robust 6-DoF detection in uncontrolled lightning enviroments
Document typeConference report
Rights accessOpen Access
One of the most critical issues that arises when controlling a robot is the necessity to locate itself in the environment. Ranging from industrial processes applications to outdoor mobile robots, landmarks are used to such purpose: by recognizing them, the robots are able to know where they are with the aid of computer vision. Fiducial markers are the cheapest and one of the most common solutions to this issue: 2D planar patterns that embed some information that can be identified using artificial vision techniques. Many different typologies of markers as well as image processing algorithms are being implemented nowadays, using C++ / Python / MATLAB® libraries and ROS as middleware. In this work we have evaluated the robustness of various fiducial marker typologies, documenting the main technical aspects of the used implementations and commenting how each algorithm operates. Aggregated results are presented and discussed, evaluating the different implementations tested.
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
CitationMora, A. [et al.]. Towards robust 6-DoF detection in uncontrolled lightning enviroments. A: IEEE International Conference on Emerging Technologies and Factory Automation. "2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA): proceedings: University of Zaragoza, Zaragoza, Spain: 10-13 September, 2019". 2019, p. 1607-1611. ISBN 978-1-7281-0303-7. DOI 10.1109/ETFA.2019.8869458.
- Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Ponències/Comunicacions de congressos [1.331]
- VIS - Visió Artificial i Sistemes Intel·ligents - Ponències/Comunicacions de congressos 
- Departament d'Enginyeria Electrònica - Ponències/Comunicacions de congressos [1.518]