Improving Hessian Approximation for Gaussian Mixture Likelihoods in Nonlinear Least Squares Optimization
The paper proposes a novel Hessian approximation for Maximum a Posteriori estimation problems in robotics involving Gaussian mixture likelihoods, which leads to better convergence properties compared to previous approaches.
