Hybrid Artificial Bee Colony and Spherical Vector-Based Particle Swarm Optimization Algorithm for UAV Path Planning

Path planning involves the goal of being able to generate a geometric path at which a mobile robot or a UAV may safely traverse across obstacles in reaching a destination. Several nature-inspired approaches have emerged, such as the spherical vector-based particle swarm optimization (SPSO) and the artificial bee colony (ABC). Utilizing each algorithm on its own poses various advantages and disadvantages. For instance, SPSO is fast and simple yet falls short as it converges at a local optimum prematurely. On the contrary, the ABC is capable of global and local searches but is typically slower in convergence. To address the issues, an integrated approach was employed using the hybrid ABC-SPSO. The algorithm was tested in an environment with varying elevations on its terrain with cylindrical obstacles. Results have shown how the proposed algorithm performs better as opposed to its traditional counterpart, as it was able to easily converge at the global optimum with lower cost function values.