Semi-automatic pose estimation of a fleet of robots with embedded stereoscopic cameras.

Cort�s, Xavier; Serratosa, Francesc; Moreno-Garcia, Carlos-Francisco

Abstract

Given a fleet of robots, automatic estimation of the relative poses between them could be inaccurate in specific environments. We propose a framework composed by the fleet of robots with embedded stereoscopic cameras providing 2D and 3D images of the scene, a human coordinator and a Human-Machine Interface. We suppose auto localising each robot through GPS or landmarks is not possible. 3D-images are used to automatically align them and deduce the relative position between robots. 2Dimages are used to reduce the alignment error in an interactive manner. A human visualises both 2D-images and the current automatic alignment, and imposes a new alignment through the Human-Machine Interface. Since the information is shared through the whole fleet, robots can deduce the position of other ones that do not visualise the same scene. Practical evaluation shows that in situations where there is a large difference between images, the interactive processes are crucial to achieve an acceptable result.

Citation

CORTÉS, X., SERRATOSA, F. and MORENO-GARCIA, C.-F. 2016. Semi-automatic pose estimation of a fleet of robots with embedded stereoscopic cameras. In Proceedings of 21st Institute of Electrical Electronic Engineers (IEEE) Emerging technologies and factory automation international conference 2016 (ETFA 2016), 6-9 September 2016, Berlin, Germany. Piscataway: IEEE [online], article ID 7733640. Available from: https://doi.org/10.1109/ETFA.2016.7733640

• Conference Name: 21st Institute of Electrical and Electronics Engineers (IEEE) Emerging technologies and factory automation international conference 2016 (ETFA 2016)
• Conference Location: Berlin, Germany
• Start Date: Sep 6, 2016
• End Date: Sep 9, 2016
• Acceptance Date: Oct 13, 2016
• Online Publication Date: Sep 9, 2016
• Publication Date: Nov 7, 2016
• Deposit Date: Oct 17, 2020
• Publicly Available Date: Oct 26, 2020
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• ISBN: 9781509013142
• DOI: https://doi.org/10.1109/ETFA.2016.7733640
• Keywords: Homography estimation; Image alignment; Interactive method; Human-robot interaction; Cooperative robotics
• Public URL: https://rgu-repository.worktribe.com/output/977243