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RoboSense Announces World’s First Public Road Test of Smart LiDAR Vehicle at CES 2020



RoboSense, the leading autonomous driving LiDAR perception solution provider, announced the world’s first public test of a vehicle equipped with a Smart LiDAR Sensor at CES 2020. The RoboSense Smart LiDAR car, featuring the award-winning RS-LiDAR-M1 Smart LiDAR, will be running outside the Las Vegas Convention Center daily during CES 2020, showing the latest technological progress in autonomous vehicle LiDAR.

Simultaneous exhibitions will be held at RoboSense’s CES Booth #6138 at the LLVC, North Hall showcasing the real-time 3D point cloud data on a vehicle equipped with the multi solid state LiDAR fusion system.

The RoboSense RS-LiDAR-M1 Smart LiDAR is the world’s first MEMS Smart LiDAR Sensor to incorporate sensor hardware, AI perception algorithms, and IC chipsets, transforming conventional LiDAR sensors from an information collector to a complete data analysis and comprehensive system, providing essential information for autonomous vehicle decision-making faster than ever before. The RS-LiDAR-M1 is the winner of the CES Innovation Award for two consecutive years in a row, 2019 and 2020.

At CES and on the streets of Las Vegas, the RoboSense RS-LiDAR-M1 Smart is demonstrating that it is the world’s first and only Smart LiDAR capable of real road tests on open roads.

During CES 2020, RoboSense128-beams LiDAR RS-Ruby and the short-range Blind Spot LiDAR RS-BPearl also go on public road demo, meanwhile there is also a simultaneous exhibition at RoboSense booth. This super high-performance 128-beam LiDAR RS-Ruby possesses an ultra high resolution 0.1° and the range performance of 200m for a 10% reflectivity target.

The RS-BPearl, the first mass produced short-range LiDAR for blind-spot detection, reaches the minimum detection range of less than several centimeters, with hemispheric FOV coverage of 90° * 360°, which not only precisely identifies objects around the vehicle’s body, but can also detect the actual height information in particular scenarios, such as with bridge tunnels and culverts.