An Improved TLBO Algorithm for Solving UAV Path Planning Problem
Soheila Ghambari, Lhassane Idoumghar, Laëtitia Jourdan, Julien Lepagnot · 2019
Typical evolutionary algorithms for Unmanned Aerial Vehicles (UAV) path planning problem represent solutions by considering a fixed number of way points, from which and by using an interpolation strategy they can generate the actual path. This paper proposed an alternative method in which the number of control points is determined during the optimization process. We investigate to what extent optimizing the number of these points during the search process could contribute to improve the results. Towards this goal, a novel approach is proposed which combines the standard teaching learning-based optimization (TLBO) with the ideas of mutation and crossover from genetic algorithm (GA). Experiments are conducted on a set of scenarios in two-dimension (2D) and three-dimension (3D) environments. The results demonstrate promising performance for solving the path planning problem of UAV.