FastSLAM Algorithm Based on Simulated Annealing for UAV

Abstract A large number of particles are needed to improve the precision of particle filtering of fast simultaneous localization and mapping (FastSLAM) for uninhabited aerial vehicle (UAV). Simulated annealing (SA) method is proposed to solve this problem. Through simulated annealing algorithm, the particle's prediction is updated and proposal distribution is adjusted in FastSLAM, so the particles are concentrated around the true pose. Stratified resampling is used to solve the degeneracy of particles. At last, the proposed algorithm is tested for UAV FastSLAM. The result shows this method is effective and feasible.