Fuzzy adaptive extended Kalman filter SLAM algorithm based on improved the wild geese PSO

For the problem of the extended Kalman filter localization and mapping algorithm priori noise model is difficult to establish ,this paper propose an improved the wild geese particle swarm algorithm based fuzzy adaptive Kalman filter localization and mapping algorithm. Take advantage of the the fractional calculus to improve particle speed of evolution, and make use of the chaos to improve the initialization of the particle and the precocious when processing. The wild geese improved particle swarm algorithm in convergence rate and avoid premature greatly improved , then improved geese particle swarm algorithm for fuzzy adaptive extended Kalman filter localization and mapping algorithm training. contrast with Geese particle swarm algorithm fuzzy adaptive extended Kalman filter simultaneous localization and mapping algorithm ,the new algorithm positioning and composition has greatly improved.