RoboSense Launches New MEMS Solid-State LiDAR at CES 2019
RoboSense, a leader in LiDAR perception technology solutions and CES 2019 Innovation Award Honoree, announced today that next week at CES 2019, they will publicly demonstrate an upgraded version of their MEMS solid-state LiDAR, an automotive grade solid-state LiDAR designed for the mass production of autonomous vehicles.
The new RS-LiDAR-M1 with patented MEMS technology offers ground-breaking vehicle intelligence awareness to fully support Level 5 driverless automated driving. A breakthrough on the measurement range limit based on 905nm LiDAR with a detection distance to 200 meters, the upgraded optical system and signal processing technology brings remarkable final output point cloud effect which can now clearly recognize even small objects, such as railings and fences.
At last year’s CES 2018, RoboSense demonstrated the first generation MEMS solid-state LiDAR RS-LiDAR-M1Pre. Just four months later, in May 2018, it was loaded on the Cainiao unmanned logistics vehicle and unveiled at the Ali CainiaoGlobal Intelligent Logistics Conference, becoming the world’s first solid-state LiDAR for unmanned vehicles. RoboSense has already been sending the MEMS LiDAR product to the world’s top OEMs and Tier 1 suppliers. At CES 2019, RoboSense will launch the new RS-LiDAR-M1, showcasing the potential of their MEMS optomechanical system design, with breakthrough improvements in detection distance, resolution, Field of View (FOV), reliability, and other RoboSense award-winning LiDAR sensing technologies.
Double the Horizontal Field of View to 120 Degrees
A major step forward from the previous version award-winning RoboSense RS-LiDAR-M1Pre, the new RS-LiDAR-M1 MEMS optomechanical LiDAR provides an increased horizontal field of view by nearly 100% compared to the previous generation, reaching an amazing 120° field of view, so that only a few RS-LiDAR-M1s are needed to cover the 360° field of view. In addition, with only five RS-LiDAR-M1s, there is no blind zone around the car with dual LiDAR sensing redundancy provided in front of the car for a L5 level of automatic driving — full driverless driving. Based on the target production cost at $200 each, the cost of five RS-LiDAR-M1 is only 1/100th the highest mechanical LiDAR available to the market, which is more inline with the cost requirements for the mass production of autonomous vehicles.
Measurement Range to 200 Meters
The battle between 1550nm and 905nm LiDAR is about cost and performance. When aiming for a low-cost 905nm LiDAR, it is necessary to overcome the technical difficulties of achieving sufficient measurement range. The RS-LiDAR-M1 achieves a breakthrough on the measurement range limit based on the 905nm LiDAR, with a detection distance to 200 meters.
A Leap Forward in Point Cloud Effect Technology — Even Small Objects
The unique RS-LiDAR-M1 LiDAR system provides massive improvements, the most remarkable being the final output point cloud effect. The M1’s detection capability is greatly improved through the upgraded optical system and signal processing technology, which can now clearly recognize even small objects,such as railings and fences.
“The RoboSense RS-LiDAR-M1 LiDAR system is a giant leap forward for driverless technology,” said Mark Qiu, Co-founder, RoboSense. “We are committed to developing high-performance automotive-grade LiDAR at a low-cost to advance the LiDAR market, so that LiDAR can be used in fully unmanned vehicles, as well as assisted autonomous driving with superior environmental information detection that ensures driving safety.”
A CES 2019 Innovation Award Honoree, the RS-IPLS first hardware and software algorithm based solution for the mass production of safer autonomous cars includes the RS-LiDAR-M1Pre first generation RoboSense MEMS LiDAR system and AI algorithms. RoboSense will be exhibiting the new upgraded MEMS LiDAR, the RS-LiDAR-M1, at CES 2019, Booth #9310, North Hall. CES is held January 8-11, 2019 at the Las Vegas Convention Center in Las Vegas, NV. For more information about RoboSense, see http://www.robosense.ai.
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