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We present an open hardware and software platform to efficiently fuse heterogeneous sensor data in an automotive/robotic context. The framework presented in this paper provides researchers a base platform in order to develop and evaluate sensor fusion strategies. In contrast to similar approaches, this framework exploits in particular the raw radar data and enables the fusion at low-level. The proposed system utilizes low-level data from radar sensors as well as indirect (e.g. 3D imaging) and direct (e.g. LIDAR) Time-of-Flight (ToF) sensors. After a configurable amount of pre-processing at sensor-level, the sensor data is transferred to a centralized platform and aligned temporally and spatially. We demonstrate the transformation of radar data into the 3D coordinate system in order to fuse it with point cloud data from ToF sensors. Due to the modular structure of the framework, it also enables the exploration of various system partitioning concepts.
|Title of host publication||Proceedings - 21st Euromicro Conference on Digital System Design, DSD 2018|
|Publisher||Institute of Electrical and Electronics Engineers|
|Number of pages||8|
|Publication status||Published - 12 Oct 2018|
|Event||21st Euromicro Conference on Digital System Design, DSD 2018 - Prague, Czech Republic|
Duration: 29 Aug 2018 → 31 Aug 2018
|Conference||21st Euromicro Conference on Digital System Design, DSD 2018|
|Abbreviated title||DSD 2018|
|Period||29/08/18 → 31/08/18|
- Automotive sensors
- Sensor fusion
ASJC Scopus subject areas
- Hardware and Architecture
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Steger, C., Seifert, C., Stelzer, P., Feldbacher, M., Fiala, G. & Basic, F.
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