Path Planning of UGV using Sampling-Based Method and PSO in 2D Map Configuration: A Comparative Analysis

The navigation system of an unmanned ground vehicle is a core research area in the field of robotics. It must be robust enough to guide UGV from source to destination through an obstacle free path. Nowadays many research are going on path planning algorithms both in a static and dynamic environment. In this paper a comparative work has been presented between sampling-based technique algorithm (PRM, bidirectional RRT) and particle swarm optimization algorithm applied in a static simple and complex environment. Sampling-based techniques use random sampling for the selection of points in the configuration space while checking not to be in obstacle configuration. The results showed that both types of techniques generated obstacle-free path in different periods. The time required by sampling-based technique is relatively less than the PSO technique. In sampling-based technique the path has vertexes at the sampled points while in PSO path consists of smooth curve which can be changed in the algorithm.