| 英文摘要 | In recent decades, with the development of computer technology, information technology and artificial intelligence technology, the mobile service robot is not only used in the traditional areas such as industry, agriculture, but also in health care, homes and so on. Path planning, global localization and trajectory tracking play an important role in the realization of autonomous mobile robots. Of the three branches, global localization, which includes the robot’s position and yaw angle, is very important to navigation and control. In this paper, on the basis of analyzing overall technical requirements and related literature, we mainly focus on solving the yaw angle of mobile robot in the global coordinate system. With the sensors of accelerometer, gyroscope, magnetometer, Extended Kalman filter is used to fuse three kinds of sensors such as accelerometer, gyroscope, magnetometer, to obtain the the precise yaw information, and a trajectory tracking decoupling controller is also designed, based on the omni-directional mobile robot’s kinematics model. In general, the main work of this paper includes following aspects: Firstly, the sensor-error calibration problem is resolved. After analyzing the sources of sensors’ predictable error, the mathematical error calibration model is established. Then we use the ellipsoid-based least square fitting method and Gauss-Newton iterative calibration method to calibrate the sensor. The calibration results of the two methods are also compared. Secondly, the micro Inertial Attitude Heading Reference System is constructed. The system is composed of gyroscope, accelerometer and three-axis magnetometer. In the system accelerometer and magnetometer are used to compensate for the gyroscope’s zero drift, and gyro is used to enhance the system’s accuracy and stability in the moving environment. The optimal attitude estimate is generated by Kalman filter. The experiment shows that system is a good choice for high-precision attitude angle. Finally, on the basis of the previous two steps, a decoupling controller based on the omni-directional mobile robot’s kinematics model is designed. In the controller, the position coordinates from passive infrared landmark visual localization module and yaw angle from sensor fusion module are regarded as feedback signals. The trajectory tracking controller has global stability. At last, we use Matlab simulation to verify the feasibility of the controller and system st... |
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