We present DQV-SLAM (Dual Quaternion Visual SLAM). This novel feature-based stereo
visual SLAM framework uses a stochastic filter based on the unscented transform and a …

We present a novel dual quaternion filter for recursive estimation of rigid body motions.
Based on the sequential Monte Carlo scheme, particles are deployed on the manifold of unit …

We propose a von Mises–Fisher sampling scheme using Fibonacci lattices to generate high-
quality deterministic samples on the sphere. Key idea is an orthogonal inverse transform to …

A novel discrete Bayesian filtering scheme is proposed on the manifold of unit quaternions
for rotation estimation. Existing quaternion filters rely on specific distributions (typically the …

We present a novel approach to stochastically model uncertain 6-DoF rigid body motions
represented by dual quaternions. Unlike conventional methods relying on the local …

In this work, we present a novel scheme for nonlinear hyperspherical estimation using the
von Mises–Fisher distribution. Deterministic sample sets with an isotropic layout are …

We present a novel deterministic sampling approach for von Mises–Fisher distributions of
arbitrary dimensions. Following the idea of the unscented transform, samples of configurable …

We propose a novel scheme for efficient Dirac mixture modeling of distributions on unit
hyperspheres. A so-called hyperspherical localized cumulative distribution (HLCD) is …

We propose a fast method for deterministic multi-variate Gaussian sampling. In many
application scenarios, the commonly used stochastic Gaussian sampling could simply be …

We propose a novel quaternion particle filter for nonlinear SO (3) estimation. For importance
sampling, the proposal distribution is designed to incorporate newly observed evidence. For …