RoboSense announced its new M Platform LiDAR sensors at CES 2024

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We are still digging through our piles of CES 2024 emails and information, trying to find some interesting news to share with you. I will admit, we are nearing the end of our pile but we did find this announcement from RoboSense that had some intriguing information about its new M Platform LiDAR sensors.

Estimated reading time: 3 minutes

Following a successful IPO on the Hong Kong Stock Exchange, RoboSense continues its drive for technological innovation by launching the M2, the ultimate mid-range LiDAR, and the M3, the M Platform’s first long-range LiDAR. These products expand the company’s robust portfolio of high-performance, cost-effective LiDAR sensors, advancing intelligent driving systems and autonomy in the automotive industry.

“This year is off to an incredible start for RoboSense, starting with our IPO and now the introduction of the cutting-edge M2 and M3 sensors,” said Mark Qiu, Executive Director and Executive President, of RoboSense. “RoboSense’s deep technical expertise and achievements in mass manufacturing enable us to develop LiDAR that is higher performance, smaller, more power-efficient, and more cost-effective. By launching the M2 and M3, we are meeting our customers’ needs, enabling seamless upgrades to their intelligent driving systems and efficient product development. The commercialization of lidar has become a reality, and we believe our M2 and M3 products will allow us to accelerate the adoption of lidar for autonomous vehicles.”

Here’s what the rest of the company’s press release had to say.

RoboSense M Platform LiDAR Sensors

M3 — The M Platform’s first long-range LiDAR sensor.

  • Uses 940 nm (nanometer) wavelengths to achieve better performance than 1550 nm lidar – the M3 costs 50-70% less, is 50% smaller, and consumes >30% less power.
  • Delivers a range of 300m at 10% reflectivity and 0.05° x 0.05° angular resolution within the region of interest (ROI) to detect smaller objects at longer distances.
  • Uses a modular design to enable performance improvement and cost reduction of next-generation models while maintaining form factor, interface, and scanning technology. Customers can upgrade their LiDAR sensors seamlessly without any design changes to their vehicles, optimizing the development cycle of intelligent driving solutions.
  • Incorporates mature and highly reliable technology for project consistency and customer trust. The company’s chip-driven technology, which is developed in house, drives high performance, fast and effective iterations, and cost efficiency.
  • The M3 is primarily designed to advance safe, intelligent driving systems for global OEM and Tier I Level 3 (L3) or higher vehicles. The M3’s ability to detect long-distance objects can meet customers’ needs for L3 functionality at up to 120 km/hour, advancing safety and autonomous features.

M2 — An iteration of the M1 and M1 Plus: high performance mid-range LiDAR.

  • Leverages proprietary 2D scanning technology and MEMS chips developed in house to achieve a range of 200m at 10% reflectivity and angular resolution of 0.1° x 0.1° in its ROI. Both range and resolution are a significant improvement over its predecessors.
  • Developed with more than 90% of the same components as the M1 Plus and shares the same technology platform and modular design, driving down costs and improving performance over each iteration.
  • The upgraded M2 maintains the same interface and design as the M1/M1 Plus, making the switch seamless for customers without costly redesign or project development delays.

RoboSense has a strong, far-reaching customer base in the automotive industry worldwide. It is the first LiDAR company to build its own chip technology, including MEMS, and the earliest to achieve mass production of automotive-grade solid-state LiDAR, according to data from CIC. As of December 18, 2023, RoboSense has obtained 62 vehicle model design wins and successfully assisted 12 OEMs and Tier 1 customers in starting the large-scale mass production delivery of 24 models.

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