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Full STEAM ahead: Exactly sparse gaussian process regression for batch continuous-time trajectory estimation on SE(3) | IEEE Conference Publication | IEEE Xplore

Full STEAM ahead: Exactly sparse gaussian process regression for batch continuous-time trajectory estimation on SE(3)


Abstract:

This paper shows how to carry out batch continuous-time trajectory estimation for bodies translating and rotating in three-dimensional (3D) space, using a very efficient ...Show More

Abstract:

This paper shows how to carry out batch continuous-time trajectory estimation for bodies translating and rotating in three-dimensional (3D) space, using a very efficient form of Gaussian-process (GP) regression. The method is fast, singularity-free, uses a physically motivated prior (the mean is constant body-centric velocity), and permits trajectory queries at arbitrary times through GP interpolation. Landmark estimation can be folded in to allow for simultaneous trajectory estimation and mapping (STEAM), a variant of SLAM.
Date of Conference: 28 September 2015 - 02 October 2015
Date Added to IEEE Xplore: 17 December 2015
ISBN Information:
Conference Location: Hamburg, Germany

References

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