碩士 / 國立成功大學 / 電機工程學系碩博士班 / 101 / The thesis describes the design, implementation, and test of an autonomous vehicle navigation system using vehicle model and particle filter tracking algorithm. Typically, a vehicle navigation system comprises of real-time environment perception, vehicle localization, collision avoidance, path planning, and path following control. In order to implement the features for intelligent autonomous vehicle, a sensor suite of integrated inertial measurement unit (IMU), GNSS receiver, and incremental encoder is developed for vehicle dynamic estimation. In the design, a map-aided path planning strategy is employed to generate a reference route. To this end, a UMI (User Machine Interface) programming on LabVIEW platform is developed to facilitate the observation of a goal-oriented path tracking performance.
In the aspect of vehicle estimation control, the system utilizes particle filter algorithm to ensure that the actual trajectory follows the planned path. The recursive particle filter is able to weight the cells and response the angle as well as estimated position information. All the sensors are integrated into an embedded computer platform to assess the autonomous driving capability. The test is conducted on campus by installing the sensor suite and embedded computer platform into an electric vehicle. The trajectory tracking capability is preliminarily verified.
| Identifer | oai:union.ndltd.org:TW/101NCKU5442240 |
| Date | January 2013 |
| Creators | Kun-JuiLi, 李堃瑞 |
| Contributors | Jyh-Ching Juang, 莊智清 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | en_US |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 79 |
Page generated in 0.0098 seconds