Path Planning of an Autonomous Mobile Robot in a Dynamic Environment\n using Modified Bat Swarm Optimization

Abstract

This paper outlines a modification on the Bat Algorithm (BA), a kind of swarm\noptimization algorithms with for the mobile robot navigation problem in a\ndynamic environment. The main objectives of this work are to obtain the\ncollision-free, shortest, and safest path between starting point and end point\nassuming a dynamic environment with moving obstacles. A New modification on the\nfrequency parameter of the standard BA has been proposed in this work, namely,\nthe Modified Frequency Bat Algorithm (MFBA). The path planning problem for the\nmobile robot in a dynamic environment is carried out using the proposed MFBA.\nThe path planning is achieved in two modes; the first mode is called path\ngeneration and is implemented using the MFBA, this mode is enabled when no\nobstacles near the mobile robot exist. When an obstacle close to the mobile\nrobot is detected, the second mode, i.e., the obstacle avoidance (OA) is\ninitiated. Simulation experiments have been conducted to check the validity and\nthe efficiency of the suggested MFBA based path planning algorithm by comparing\nits performance with that of the standard BA. The simulation results showed\nthat the MFBA outperforms the standard BA by planning a collision-free path\nwith shorter, safer, and smoother than the path obtained by its BA counterpart.\n