Path planning for unmanned aerial vehicle based on genetic algorithm

Path planning for unmanned aerial vehicle based on genetic algorithm & artificial neural network in 3D

“…So GA attempts to find the minimum value of the variable for which the entire fitness function's value is found to be minimum in a globally optimum way [1]. That means it finds the value of variables involved in the fitness function so that the value of the function obtained is minimum.…”

“…Among them Evolutionary Algorithms are used to form the strategy of path planning in a natural manner [1]. In [1] a technique has been presented for UAV path planning in an adversarial environment in which Genetic Algorithms based optimization techniques are used to plan a path which is shortest in length and distance of UAV from obstacle is maximum. The obstacle can be radar [1].…”

“…Then three operations of selection, crossover and mutation are performed over the population consisting of set of solutions and then the new set of solutions is produced which is assumed to be better than the previous generations. The process is repeated many times till the final solution is arrived which is also known as the final generation [1].…”

“…At any given generation, the population consists of set of chromosomes or paths. The GA works by employing the operators to produce new paths which are assumed to be better than the previous set of paths from the previous generation [1].…”

“…The algorithm proposed in [1] consists of several steps: initial set of population is generated randomly consisting of several solutions. Here the solution is the path which the UAV can follow to move from one position to another position safely.…”