A Self-Localization Method for Urban Environments using Vehicle-Body-Embedded Off-the-Shelf Sensors
| Autor: | Abdelaziz Khiat, Chikao Tsuchiya, Takeda Yuichi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Computer science Real-time computing Satellite system 02 engineering and technology Signal 020901 industrial engineering & automation Interference (communication) GNSS applications Self localization 0202 electrical engineering electronic engineering information engineering Off the shelf 020201 artificial intelligence & image processing Point (geometry) Urban environment |
| Zdroj: | 2019 IEEE Intelligent Vehicles Symposium (IV). |
| DOI: | 10.1109/ivs.2019.8813785 |
| Popis: | The Global Navigation Satellite System (GNSS) is by far the most used system for vehicle self-localization. However, it often fails in urban environments because of signal outages and other interference. To overcome this issue, roof-mounted LiDARs are often used by autonomous driving system developers. From a design point of view, such sensors are not appealing to the public users. Body-embedded sensors do not provide enough information because of placement and size constraints. In this paper, we show how to overcome all these constraints and achieve highly acceptable accuracy allowing reliable autonomous behavior. The proposed method's validity was demonstrated by an autonomous vehicle run in a typical urban environment. |
| Databáze: | OpenAIRE |
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