Sunflower optimization algorithm based steering angle controlled motion planning of two-wheeled Pioneer P3-DX robot in V-REP scenario

Abstract

Motion planning problems of a wheeled robot remain challenging for the researchers and are being solved by applying various nature-inspired algorithms. Therefore, this article implements the sunflower optimization algorithm and tries to solve the motion control and planning of a wheeled robot. A sunflower optimization algorithm is a newly invented algorithm, and it is inspired by the motion of sunflowers to capture solar radiation. In this study, the differential driven two-wheeled Pioneer P3-DX (P3D) robot has been chosen for experiments. The real-time ultrasonic sensors data (obstacles distance) information have been taken as inputs of the algorithm, and the steering control angle of the P3D robot is an output of the algorithm. The objective function of the algorithm has been made by taking these inputs and output data. Further, the implemented algorithm has been tested in the Virtual Robot Experimentation Platform (V-REP) software scenarios on differential driven two-wheeled P3D robot. Next, this implemented algorithm has been compared with previously developed particle swarm optimization algorithm to verify the effectiveness and authenticity of the implemented algorithm.