Robot Path Planning via Harris Hawks Optimization: A Comparative Assessment

摘要

Path planning is the task of finding a safe and efficient path for a mobile robot to navigate through an environment while taking into account factors such as energy efficiency and time constraints. This study compares the performance of the Harris Hawks optimization (HHO)-based method with other competing swarm intelligence algorithms such as Whale optimization Algorithm, Sine Cosine Algorithm, and Multi-Verse optimizer Algorithm. By including safety and path length in the cost function, and imposing a constraint on the processing time, simulation results demonstrate that the HHO-based path planning method is able to drive the robot towards the target with the lowest path cost compared to the rest.