PTP Tracking Scheme for Indoor Surveillance Vehicle by Dual BLACM With Hall Sensor

Abstract

This article presents point-to-point tracking error reduction algorithm for indoor surveillance vehicle, which is driven by two in-wheel brushless ac (BLac) motors. In general, in order to control the position, additional equipment such as a separate sensor, camera, or GPS to know the absolute or relative position of the vehicle is required. However, when a large number of sensors or expensive equipment is used, the overall price of the system will also increase, which creates a problem. Also, Global Positioning System cannot be used in indoor systems due to poor signal reception. In the proposed method, the position tracking of the autonomous vehicle only adopts the hall sensor of the traction BLac motors and a gyro sensor on the controller, without any absolute position detecting sensors. From the estimated heading angle by the inertia measurement unit sensor and the calculated moving distance by the hall sensor, the tracking path and actual moving distance errors can be estimated in the proposed method. The actual real-time moving path error is compensated by adjusting the speed and heading angle in the presented control method. Through various experiments, it is verified that the position tracking performance of the indoor autonomous vehicle is improved using the proposed method.