A novel method for computation of importance weights in Monte Carlo localization on line segment-based maps
Monte Carlo localization has rarely been studied on line segment-based maps. Importance weights play a key role in the performance of Monte Carlo localization. A heuristic-driven method for weight computation on segment-based maps is proposed. The proposed method is compared with three other weight computation methods. Results corroborate that the proposed method is more accurate, robust and efficient.
importance weight monte carlo localization line-segment map particle filter pose tracking