CES 2020: RoboSense Smart LiDAR Car Features MEMS Smart LiDAR with Built-in AI Algorithm Perception Results

RoboSense announced at CES 2020 what it claimed was the world’s first public road test of a vehicle equipped with a Smart LiDAR Sensor. The RoboSense Smart LiDAR car, featuring RS-LiDAR-M1 Smart LiDAR, was running outside the Las Vegas Convention Center daily during CES, showing the latest technological progress in autonomous vehicle LiDAR.

RoboSense also believes that its RS-LiDAR-M1 Smart LiDAR is the world’s first MEMS Smart LiDAR Sensor to incorporate sensor hardware, AI perception algorithms, and IC chipsets, and said that this transforms conventional LiDAR sensors from an information collector to a complete data analysis and comprehension system, providing essential information for autonomous vehicle decision-making faster than ever before.

RoboSense Co-Partner and Vice President Dr. Leilei Shinohara, said, “Based on extensive data optimization, RoboSense’s algorithm performance and software stability and reliability have proven to have many key advantages. Developed by RoboSense after more than a decade of exhaustive research in perception technology, it has combined the deep learning-based AI algorithm performance advantages with traditional algorithms to provide functional safety. Since 2017, RoboSense’s algorithms have gained more than 100 global partners for various types of autonomous driving scenario certifications.”

RS-LiDAR-M1 apparently provides high-resolution 3D point cloud data faster than traditional LiDAR and outputs structured semantic-level comprehensive environment information in real-time, including RoboSense’s own high-precision positioning, free space detection, dynamic object tracking, and obstacle detection, identification, and classification for autonomous vehicle decision-making, improving autonomous driving safety.

The final serial production version of the RS-LiDAR-M1 Smart will include additional functions, such as automatic calibration, window fog detection, sleep mode, and automatic wake-up to further improve autonomous driving feasibility and safety, saving time on maintenance.