A novel path planning algorithm for mobile robot in dynamic environments using modified bat swarm optimization

This paper describes the path planning of an autonomous mobile robot using an advanced version of the swarm bat algorithm in a time-varying situation. The foremost objective of this present contribution is to acquire the shortest path between the initial and end-point avoiding dynamic obstacles. In this work, an adaptation of the frequency parameter of the standard bat algorithm to develop an improved version known as the modified frequency bat (MFB) algorithm is proposed. The modified frequency bat algorithm works in two steps, in the first step, the robot path is generated when there are no obstacles in the environment using the proposed method. As soon as an obstacle is detected near the robot, the second mode is initiated to avoid any obstacle. Extensive simulations are performed to validate the effectiveness of the proposed modified frequency bat algorithm by implementing it on standard benchmark functions and path planning problems and simultaneously matching its performance with the original bat algorithm. It has been concluded that the modified frequency bat algorithm shows superior performance as compared to the standard bat algorithm by drawing a shorter and collision-free path for the mobile robot path-planning problem.