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Xylon's Innovations at CAR-ELE Japan

Dec. 28, 2017 – As the renown Xilinx partner, Xylon will be exhibiting at the Xilinx booth E54-47 during the upcoming CAR-ELE Japan 2018 – the World's largest exhibition specialized in automotive electronics!

At the exhibition Xylon will present the new logiRECORDER 3.0 Automotive Video Data Logger to the Japanese market for the first time. Previous versions of the data logger have been already highly rated in Japan, and in regards to a significantly improved flexibility and the expanded features set of the logiRECORDER 3.0, we expect even better feedback and quick deployment in local R&D, and test and validation test vehicle fleets.

 

The third-generation logiRECORDER video data logger now can support any automotive video interface, has support for vehicle interfaces expanded by the Ethernet and BroadR-Reach® networks, as well as the wireless communication links. Simultaneous video and networks data playback now makes Hardware-in-the-Loop (HIL) lab simulations even more accurate. The intuitive dashboard PC application is upgraded with user-defined text and graphics markers that enable i.e. traffic signs marking in the video footage. The last but not least, the new logiRECORDER 3.0 comes in newly developed and extra rugged housing.


Besides the presentation of the new logiRECORDER automotive logger, Xylon IP cores and software libraries for the Structure from Motion (SfM) 3D space reconstruction around the moving car, or self-guided robot, will have its world premiere. This Xylon SfM IP suite, which runs on the Xilinx Zynq-7000 AP SoC and Zynq UltraScale+ MPSoC devices, makes one of the key technologies for ADAS and Autonomous Driving.

It enables use of the optical cameras mounted on the vehicle, which are regularly used for already established ADAS applications like the surround view parking assistance application, to be used as inexepensive sensors for 3D mapping of the vehicle's surrounding. The generated 3D maps can be used alone for detection of objects around the vehicle, for example in self-parking and self-braking applications, or correlated by the data produced by non-optical sensors in sensor fusion that improves ADAS/AD accuracy and reliability.

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