Takumi Nakao

Range-Based 6-DoF Monte Carlo SLAM with Gradient-Guided Particle Filter on GPU

This paper presents range-based 6-DoF Monte Carlo SLAM with a gradient-guided particle update strategy. While non-parametric state estimation methods, such as particle filters, are robust in situations with high ambiguity, they are known to be unsuitable for high-dimensional problems due to the curs