Unmanned aerial vehicles (UAVs) are a quintessential example of automation in the field of avionics. UAVs provide a platform for performing a wide variety of tasks, but in each case, the concept of path planning plays an integral role. It helps to generate a pathway free of obstacles, having minimum length, leading to lesser fuel consumption and lesser traversal time.

To optimize path planning and to incorporate all the above-mentioned constraints, this paper presents two new hybrid algorithms particle swarm optimization (PSO) with harmony search algorithm and PSO with genetic algorithm. The hybrid algorithms perform both an exploratory and exploitative search, unlike the existing algorithms which are biased towards either an exploitative search or an exploratory search.