Mobile Robot Navigation in Cluttered Environment Using Spider Monkey Optimization Algorithm

Swarm intelligence is one of the most emerging methods used for autonomous mobile robot navigation. Researchers have developed many algorithms in mobile robot navigation by simulating the swarming behavior of various creatures like ants, firefly, honey bees, and cuckoo, and the findings are very motivating. The paper presents application and implementation of spider monkey optimization (SMO) along with Three Path method (TPM) for mobile robot navigation in cluttered environment. A collision-free path is selected by using TPM. When all the three paths are blocked by obstacles, SMO is used for obstacles avoidance. The finding of global and local leaders from the groups is the key concept of the proposed method. The proposed method efficiently improves the global search in less number of iterations, and hence, it can be easily implemented for real-time obstacle avoidance. The computational path and time are less as compared to other navigational methods. Some simulation results are presented at the end of the paper to show the effectiveness of the proposed navigational method.