Dynamic Modeling and Simulation of a Four-wheel Skid-Steer Mobile Robot using Linear Graphs

TL;DR

This paper introduces a linear graph-based modeling approach for a four-wheel skid-steer robot, validated through simulation and real-world experiments, demonstrating high accuracy in system representation.

Contribution

It develops a novel linear graph representation and employs genetic algorithms for parameter estimation, enhancing the accuracy of mobile robot modeling and simulation.

Findings

LG model closely matches experimental data

GA improves parameter accuracy

Model validated against Gazebo simulation

Abstract

This paper presents the application of the concepts and approaches of linear graph (LG) theory in the modeling and simulation of a 4-wheel skid-steer mobile robotic system. An LG representation of the system is proposed and the accompanying state-space model of the dynamics of a mobile robot system is evaluated using the associated LGtheory MATLAB toolbox, which was developed in our lab. A genetic algorithm (GA)-based parameter estimation method is employed to determine the system parameters, which leads to a very accurate simulation of the model. The developed model is then evaluated and validated by comparing the simulated LG model trajectory with the trajectory of a ROS Gazebo simulated robot and experimental data obtained from the physical robotic system. The obtained results demonstrate that the proposed LG model, combined with the GA parameter estimation process, produces a highly accurate method of modeling and simulating a mobile robotic system.