  Localization is a fundamental requirement for an autonomous vehicle system.
One of the most often used systems for autonomous vehicle localization is the
global positioning system (GPS). Nevertheless, the functionality of GPS is
strongly dependent on the availability of satellites, making it unreliable in
some situations. As a result, autonomous vehicles must possess autonomous
self-localization capabilities to ensure their independent operation. Odometry
techniques are employed to achieve vehicle localization by predicting the
vehicle position and orientation based on sensor measurements of the vehicle
motion. One of the approaches employed in odometry is known as wheel odometry.
Wheel odometry has a lower degree of reliance on the surrounding environment
than visual odometry and laser odometry. This study aims to evaluate the
performance of wheel odometry implementation for an autonomous wheelchair in
the context of the localization process. The differential drive kinematic model
is employed to determine the predicted pose of a wheelchair. This prediction is
derived from the measurement of the linear and angular velocity of the
wheelchair. Several experiments have been conducted to evaluate the performance
of wheel odometry-based localization. Prior to experimenting, calibration
procedures have also been performed to ensure accurate measurements of the
sensor.
