Tactical Path Planning Method for Military Unmanned Vehicle in Battlefield
Zhao Han-qing · Journal of Academy of Armored Force Engineering · 2012
A novel algorithm of improved Particle Swarm Optimization(PSO) based on threat cost map is proposed for military unmanned vehicle tactical path planning in battlefield existing different types of threats.The path is described by some key points'polar angle in polar coordinates,and it is smoothed by piecewise cubic Hermite interpolation method,thus the path planning is equivalent to parameter optimization of polar angles.Because Basic Particle Swarm Optimization(BPSO) is easy to fall into the local optimum as the swarm activity of population gets worse during the evolution,an improved PSO based on the Multi-tasking Subpopulation Cooperation(PSO-MSC) is developed by introducing the idea of multi-tasking subpopulation mechanism used by gregarious species.PSO-MSC is introduced to get the optimal path for its fast convergence and global search character.Experimental results show that a safe and smooth tactical path can be found fleetly and effectively in complicated battlefield environment by the proposed method.