Toronto Metropolitan University
Nonparametric_Bootstrap_Technique_to_Improve_Positional_Accuracy_in_Mobile_Robots_With_Differential_Drive_Mechanism.pdf (1.8 MB)

Nonparametric Bootstrap Technique to Improve Positional Accuracy in Mobile Robots With Differential Drive Mechanism

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journal contribution
posted on 2023-07-24, 18:02 authored by Yaser Maddahi, Kourosh ZareiniaKourosh Zareinia

Wheeled mobile robots (WMRs) inevitably experience positional inaccuracy, which is caused by a number of factors including design imperfections, problems with component fabrication, sensor errors, and electromechanical malfunction. We have previously proposed an odometry-based technique that reduces positional inaccuracy in WMRs driven with standard wheels. This technique combines high sampling rates and short-term accuracy, and calculates necessary lateral and longitudinal corrections by using linear regression to model the relationship between positional inaccuracy and angular velocities of the robot's wheels. This technique can do so without the precision of measurement required by other techniques. In this paper, we discuss how a nonparametric bootstrap approach can be used to find both interval and point estimates of the modified angular velocities required to alleviate the positional inaccuracy of the WMR. First, the robot travels along a path recommended by the odometry-based error reduction technique. Then, the positional and angular errors of the robot at the stop point are measured. Next, these measurements are used to estimate angular velocities, providing the necessary confidence intervals (prediction). Results from these calculations could be incorporated into the robot program to modify the movement along a given path (validation). To show viability, the bootstrap technique was applied to a prototype mobile robot while the robot was programmed to move along an unseen trajectory. Results indicate that, for this typical unseen path, the bootstrap technique is capable of improving real-time positional systematic and non-systematic inaccuracy with acceptable levels of precision compared to the linear regression technique under the normality assumption. The bootstrap technique exhibited better efficacy than the linear regression, therefore, it may be a useful tool to conduct real-time calibration of differential drive WMRs.




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