Vision based passive arm localization approach for underwater rovs using a least squares on SO(3) gradient algorithm

Chandra P. Mangipudi, Perry Y Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a vision based alternative to the passive arm pose estimation for underwater remotely operated vehicle (ROV) performing manipulation tasks. The proposed approach attaches a fixed landmark on an underwater fixture and uses the camera images of the landmark object points to infer the pose of the ROV. A gradient descent least squares algorithm on the SO(3) manifold is proposed for accurately and efficiently estimating the pose. The algorithm has been implemented on a low-cost single board computer. Numerical comparison with other existing algorithms as well as in-air and underwater experiments show the efficacy of the algorithm. Positional accuracy of the order of 1-2.5mm while the landmark is approximately 1m away has been demonstrated.

Original languageEnglish (US)
Title of host publication2019 American Control Conference, ACC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5798-5803
Number of pages6
ISBN (Electronic)9781538679265
StatePublished - Jul 2019
Event2019 American Control Conference, ACC 2019 - Philadelphia, United States
Duration: Jul 10 2019Jul 12 2019

Publication series

NameProceedings of the American Control Conference
Volume2019-July
ISSN (Print)0743-1619

Conference

Conference2019 American Control Conference, ACC 2019
CountryUnited States
CityPhiladelphia
Period7/10/197/12/19

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Mangipudi, C. P., & Li, P. Y. (2019). Vision based passive arm localization approach for underwater rovs using a least squares on SO(3) gradient algorithm. In 2019 American Control Conference, ACC 2019 (pp. 5798-5803). [8815230] (Proceedings of the American Control Conference; Vol. 2019-July). Institute of Electrical and Electronics Engineers Inc..