With the increase of social concern about the disables and elderly people, their participation in social activities is demanded. In this view, an intelligent wheelchair is necessary for giving them better mobility and for saving them a considerable physical effort. To control the motion of the intelligent wheelchair, the current position of the wheelchair must be known as accurately as possible. A well-known method to estimate the current position in the field of wheeled mobile robotics is dead- reckoning. But in the case of the position estimation based on the conventional dead-reckoning for an intelligent wheelchair with pneumatic tires, it is impossible to avoid the position estimation error because of the change of radii of the wheels which depend on an user's weight and a variable environment.
Therefore, this thesis proposes the positioning system which can estimate the error of radii of the wheels using a gyroscope and ultrasonic sensors and can correct the radii of the wheels to reduce the dead-reckoned position error. The extended Kalman filter was used as a method for fusing multisensor data with information on the dead-reckoned position error.
Simulations to verify the effectiveness of the proposed positioning system are performed and they prove good performances demonstrated from the results.