Development of Autonomous Driving Systems Using State Estimator with Multi-rate Sampled-data
| Autor: | Seungyong Han, Sang-Moon Lee, Jongpil Yun, Eungchang Mason Lee, Crino Shin, Yongsik Jin |
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| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Unmanned ground vehicle Computer science 020208 electrical & electronic engineering Sampling (statistics) Ranging 02 engineering and technology Tracking (particle physics) 020901 industrial engineering & automation Lidar Control theory 0202 electrical engineering electronic engineering information engineering Development (differential geometry) Affine transformation Encoder |
| Zdroj: | ICCE |
| DOI: | 10.1109/icce.2019.8661985 |
| Popis: | This paper presents a state estimator design method using multi-rate sampled-data for autonomous vehicle driving system. The proposed state estimator is designed by using an affine matched T-S fuzzy model with the sampling information of each sensors. For the tracking control of autonomous driving system with fusion sensors, overall control structure is designed by using the error dynamic model based state estimator. The proposed method is verified by the experimental results on the Husky unmanned ground vehicle (UGV) equipped with light detection and ranging (LiDAR), camera and encoder. |
| Databáze: | OpenAIRE |
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