A Novel Hybrid Particle Swarm Optimization Algorithm for Path Planning of UAVs

Automatic path planning problem is essential for efficient mission execution by unmanned aerial vehicles (UAVs), which needs to access the optimal path rapidly in the complicated field. To address this problem, a novel hybrid particle swarm optimization (PSO) algorithm, namely, SDPSO, is proposed in this article. The proposed algorithm improves the update strategy of the global optimal solution in the PSO algorithm by merging the simulated annealing algorithm, which enhances the optimization ability and avoids falling into local convergence; each particle integrates the beneficial information of the optimal solution according to the dimensional learning strategy, which reduces the phenomenon of particles…

• NS
  National Science Foundation

  Award: 2150213
• NN
  National Natural Science Foundation of China

  Award: 61873277