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SE(n)++: An Efficient Solution to Multiple Pose Estimation Problems | IEEE Journals & Magazine | IEEE Xplore

SE(n)++: An Efficient Solution to Multiple Pose Estimation Problems


Abstract:

In robotic applications, many pose problems involve solving the homogeneous transformation based on the special Euclidean group {\mathrm{ SE}}(n) . However, due to the...Show More

Abstract:

In robotic applications, many pose problems involve solving the homogeneous transformation based on the special Euclidean group {\mathrm{ SE}}(n) . However, due to the nonconvexity of {\mathrm{ SE}}(n) , many of these solvers treat rotation and translation separately, and the computational efficiency is still unsatisfactory. A new technique called the {\mathrm{ SE}}(n)++ is proposed in this article that exploits a novel mapping from {\mathrm{ SE}}(n) to {\mathrm{ SO}}(n + 1) . The mapping transforms the coupling between rotation and translation into a unified formulation on the Lie group and gives better analytical results and computational performances. Specifically, three major pose problems are considered in this article, that is, the point-cloud registration, the hand–eye calibration, and the {\mathrm{ SE}}(n) synchronization. Experimental validations have confirmed the effectiveness of the proposed {\mathrm{ SE}}(n)++ method in open datasets.
Published in: IEEE Transactions on Cybernetics ( Volume: 52, Issue: 5, May 2022)
Page(s): 3829 - 3840
Date of Publication: 02 September 2020

ISSN Information:

PubMed ID: 32877345

Funding Agency:


References

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