Short Title: Int. J. Mech. Eng. Robot. Res.
Frequency: Bimonthly
Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
2024-10-25
2024-09-24
Abstract—Pose estimation for mobile robots depends basically on accurate odometry information. Odometry from the wheel's encoder is mostly used for simple and inexpensive implementationfor determining the relative position of a mobile robot. This paper deals with the determination of better relative localization of a two wheeled differential drive robot by means of odometry by considering the influence of parameters namely payload, speed, diameter of wheel and thickness of wheel. Experiments have been conducted based on central composite rotatable design matrix. A mathematical model has been developed for the robot using Response Surface Methodology (RSM) with the help of MINITAB software. An optimum relative positioning was obtained by using Genetic Algorithm (GA). Index Terms—Mobile robot, Odometry, Relative localization, Response surface methodology, Genetic algorithm
Cite: T Mathavaraj Ravikumar, R Saravanan, and N Nirmal, "Optimization of Relative Positioning in a Two Wheeled Differential Drive Robot," International Journal of Mechanical Engineering and Robotics Research, Vol. 3, No. 1, pp. 1-11, January 2014.