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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...
This paper proposes using hierarchical wavelets as a basis in parametric continuous-time batch estimation. The need for a continuous-time robot pose in the simultaneous localization and mapping (SLAM) problem has arisen as state-of-the-art batch SLAM algorithms attempt to handle more challenging hardware; specifically, the continuous-time framework is particularly beneficial when using high-rate sensors,...
Appearance-based batch nonlinear optimization techniques for simultaneous localization and mapping (SLAM) have been highly successful in assisting robot motion estimation. Traditionally, these techniques are applied in a single privileged coordinate frame, which can become computationally expensive over long distances, particularly when a loop closure requires the adjustment of many pose variables...
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