Work

Path Planning of an autonomous Mobile Robot using Swarm Based Optimization Techniques

Year: 2017

Type: article

Abstract: This paper presents a meta-heuristic swarm based optimization technique for solving robot path planning. The natural activities of actual ants inspire which named Ant Colony Optimization. (ACO) has been proposed in this work to find the shortest and safest path for a mobile robot in different static environments with different complexities. A nonzero size for the mobile robot has been considered in the project by taking a tolerance around the obstacle to account for the actual size of the mobile robot. A new concept was added to standard Ant Colony Optimization (ACO) for further modifications. Simulations results, which carried out using MATLAB 2015(a) environment, prove that the suggested algorithm outperforms the standard version of ACO algorithm for the same problem with the same environmental conditions by providing the shortest path for multiple testing environments.

Source: Al-Khwarizmi Engineering Journal

DOI: 10.22153/kej.2016.08.002

Authors: Ibraheem Kasim Ibraheem, Fatin Hassan Ajeil

Institution: University of Baghdad

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $80