How does the M1 perform in heavy snow, cold wind weather (-18℃~-23℃)?

March 25, 2021, Shenzhen, RoboSense (https://robosense.ai/), the automotive-grade smart LiDAR supplier, today released a sensing performance test video of the automotive-grade solid-state LIDAR RS-LiDAR-M1 (the SOP version) in extremely challenging snowy cold weather (-18℃~-23℃) in China’s northeast region. It is also the first cold winter test of automotive-grade solid-state LiDAR.

The RS-LiDAR-M1 were mounted and tested on the passenger car and the L3 heavy-duty freight truck of Inceptio Technology in China’s northeast region including Yakeshi, Inner Mongolia, and Heihe, Heilongjiang. …

Integrating LiDAR scanners into self-driving vehicles is undoubtedly the most discussed topic in the field of intelligent driving in 2021. It’s a uniform understanding of the automotive industry that the excellent perception capability of 3D LiDAR sensor will make autonomous driving and smart transportation safer and more comfortable.

However, the questions are how much the added high-resolution LiDAR can help to improve the perception capability of the whole intelligent perception system? Will it meet the expectation of the industry? How exactly is the overall performance of the multi-sensor fusion system of 3D laser LiDAR, camera and millimeter-wave radar?

The best…

RoboSense And Inceptio Announced Cooperation On Mass Production Of L3 Heavy-duty Trucks

Shenzhen (China), March 12, 2021 — RoboSense(https://robosense.ai/) announced the launch of China’s first automotive-grade solid-state LiDAR production line and would start mass production and delivery of the automotive-grade solid-state LiDAR RS-LiDAR-M1 for contract projects in Q2 this year.

At the CES2021 in January this year, RoboSense has officially unveiled the SOP version of the automotive-grade LiDAR RS-LiDAR-M1, which features a slim design, excellent performance, and reliable point cloud quality. Since July last year, the RS-LiDAR-M1 has successively received a number of orders for mass-production vehicle models around the…

Shenzhen (China), March 12, 2021 — RoboSense(https://robosense.ai/) announced the launch of China’s first automotive-grade solid-state LiDAR production line and would start mass production and delivery of the automotive-grade solid-state LiDAR RS-LiDAR-M1 for contract projects in Q2 this year.

At the CES2021 in January this year, RoboSense has officially unveiled the SOP version of the automotive-grade LiDAR RS-LiDAR-M1, which features a slim design, excellent performance, and reliable point cloud quality. Since July last year, the RS-LiDAR-M1 has successively received a number of orders for mass-production vehicle models around the world, among which, the first customer was an OEM from North America…

How 3D laser LiDAR solve the problems of autonomous vehicle’s near-field detection of blind spots?

According to the global status report on road safety from the World Health Organization, approximately 1.35 million people died in traffic accidents in 2018, and 3,700 people died in car accidents every day, that’s to say, around 3,700 people died in car accidents every day. Nevertheless, almost all of these injuries and deaths were caused by human error. As one of the most important future technologies in the 21st century, we believe that self-driving cars will effectively eliminate accidents that are caused by human error.

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RS-Reference 2.1 Can Efficiently Evaluate the Performance of the LiDAR and Multi-Sensor Fusion Sensing System

[Shenzhen, China] — RoboSense LiDAR (https://robosense.ai/) today released the latest version of the ground truth data system and evaluation tool chain RS-Reference 2.1, used for LiDARs and multi-sensor fusion systems performance evaluation. The original RS-Reference version was launched in the market in 2016, when the automotive-grade MEMS solid-state LiDAR RS-LiDAR-M1 project was established. Used by global OEMs and Tier1s, the system has been continuously improved and upgraded with more efficient and useful evaluation function modules and software tool chains.

While the evaluation function modules can…

Point Cloud Quality Is The Key Criteria in Evaluating LiDAR Performance

When talking about 3D LiDAR performance, it’s universally agreed that the parameters of LiDAR are important. Nevertheless, parameters are just the “fundamentals”! When working in complex traffic scenarios, LiDAR for self-driving cars needs to tackle various extreme working conditions comprised of high reflectivity objects, near-field obstacles, strong ambient light (direct sunlight), and interference from other LiDAR sensors, etc., which any of them may cause abnormal to the point cloud that may “fool” the processing algorithms and furthermore lead to tragic accidents. These extreme working conditions are “Corner Case”. …

The Five Key Aspects Of A Mass-Production-Ready, Automotive-Grade, Solid-State LiDAR

From demo to production, different product stages have different requirements for LiDAR’s mechanical design, hardware, software, validation, verification and reliability. For automotive LiDAR, it usually takes several years to move from a concept to a stable mass production product in order to support the complete commercial autonomous vehicles.

After five years’ investments in iterations of five major stages and dozens of small stages, RoboSense has finally announced at the CES2021 and demonstrated the SOP version of the automotive-grade MEMS solid-state LiDAR RS-LiDAR-M1 (referred to as “RoboSense M1”). …