Dr. Leilei Shinohara, Vice President of R&D at RoboSense – Interview Series

Dr. Leilei Shinohara is Vice President of R&D, RoboSense. With more than a decade of experience developing LiDAR systems, Dr. Shinohara is one of the most accomplished experts in this field. Prior to joining RoboSense, Dr. Shinohara worked at Valeo as the Technical Lead for the world’s first automotive grade LiDAR, SCALA®. He was responsible for multiple programs, including automotive LiDAR and sensor fusion projects. Dr. Shinohara managed an international sensor product development team for the development and implementation of systems, software, hardware, mechanics, testing, validation, and functional safety to build the first automotive grade LiDAR product.

Prior to joining Robosense as Vice President of R&D you had more than a decade of experience in developing LiDAR, including having worked with Valeo's SCALA® LiDAR project. What was it that attracted you to joining Robosense?

RoboSense is Asia’s No.1 LiDAR with the amazing development speed.

Prior to joining RoboSense, I was impressed by the innovation capabilities and technical acumen of RoboSense. RoboSense is targeting to be the top smart LiDAR sensor provider to the automotive market, which not only about the LiDAR HW but also the AI perception algorithm. This goal is quite fitting with my vision for the future smart sensor approach. At CES 2019, RoboSense exhibited its latest MEMS solid-state LiDAR, which has superior performance to its peer products. At CES 2020, RoboSense made huge progress and announced that the solid-state LiDAR RS-LiDAR-M1 is ready for sale with price of $1,898.

“At CES 2019, RoboSense exhibited its latest MEMS solid-state LiDAR, which has superior performance to its peer products. At CES 2020, RoboSense made huge progress and announced that the solid-state LiDAR RS-LiDAR-M1 is ready for sale with price of $1,898.”

With RoboSense’s leading technology and my previous experience in the automotive industry, I am confident that together, we can greatly accelerate the development of automotive-grade LiDAR products that can be mass-produced to make highly automated driving a reality.

 

It’s important to understand the benefits of LiDAR technology for autonomous vehicles versus regular camera systems. Could you want us through some of these benefits?

Cameras and radar have their limitations. For example, cameras don’t work well under bad ambient light conditions and radar has limitations detecting the stationary obstacle. Compared to the camera, LiDAR’s biggest advantage lies in higher accuracy and precision. It is not affected by the ambient light conditions, such as night, bright sunlight or the oncoming headlights of other cars, and able to work in various complex traffic conditions.

Recently we know quite some news about the tesla autopilot accident. As we know, Tesla’s autopilot system only relies on the Camera and Radar. Those accidents also prove that LiDAR is critical to guarantee the safety and compensate for the weaknesses that currently occur with conventional sensors.

“Those accidents also prove that LiDAR is critical to guarantee the safety and compensate for the weaknesses that currently occur with conventional sensors.”

Both Audi’s A8 (a Level 3 mass-produced autonomous vehicle) and the Waymo One (an autopilot ride-hailing service) have used LiDAR, which is an important industry indicator. Level 3 autonomous passenger vehicles using LiDAR will gradually become the industry standard.

 

One of the common complaints that we hear about LiDAR is that it’s too expensive for the bulk of consumer vehicles. Do you feel that the price will eventually drop to make it more competitive?

As we all know, high cost is one of the major limits for traditional LiDAR systems to meet mass production, it is an inevitable trend that LiDAR price will eventually drop to meet consumer autonomous vehicle’s needs. Currently, our MEMS LiDAR using a MEMS micromirror to steer the laser beam for scanning can feasibly be made small and at a lower cost，which makes it more competitive to overpriced Mechanical LiDAR.

“Currently, our MEMS LiDAR using a MEMS micromirror to steer the laser beam for scanning can feasibly be made small and at a lower cost，which makes it more competitive to overpriced Mechanical LiDAR.”

RoboSense MEMS-based LiDAR M1 uses 905nm lasers with low cost, automotive grade, and compact size. Parts have reduced from hundreds to dozens in comparison to traditional mechanical LiDARs, greatly reducing the cost and shortening production time– achieving a breakthrough in manufacturability. The coin-sized optical module processes the optical-mechanical system results to meet autonomous driving performance and mass production requirements.

The M1’s prototype with a 200m detection range and equivalent to 125 layers now sells with a price of $1,898 in comparison with the conventional 128 layers mechanical LiDAR which costs ten thousand dollars. Furthermore, when we are moving to the volume mass-production, the sensor cost can drop to a range of $200.

 

In December 2019, Robosense announced its launch of a developed and complete LiDAR perception solution for Robo-Taxi (RS-Fusion-P5). What is this solution?

“The RS-Fusion-P5 equipped with RoboSense’s flagship mechanical LiDAR model RS-Ruby and four short range blind-spot LiDAR RS-Bpearl. The multiple LiDAR fusion perception solution is developed for further accelerating the development of Robo-Taxi.”

The RS-Fusion-P5 has excellent perception capabilities. It is able to reach 200m detection range for a 10% reflectivity target, and with up to 0.1° high-precision resolution with full coverage, zero blind spots in the sensing zone. In addition, through its advanced AI perception algorithms, multi-sensor fusion, and synchronization interfaces, vehicles are able to identify all-around obstacles and position easily and precisely, empowering Level 4 or above autonomous vehicles with full-stack perception Capabilities.

The embedded four RS-BPearl form a hemispherical FOV coverage of 90° * 360° (or 180° * 180°), which not only can precisely identify objects around the vehicle body such as pets, children, roadbeds as well as other details of the near-field ground area but also detect the actual height information under particular scenarios such as bridge tunnels and culverts, further supporting autonomous vehicles for driving decision making and greatly improving car safety.

 

The RS-Fusion-P5 has zero blind spots in the sensing zone. How is this achieved?

To cover the blind spot zone, as following picture shows, 4x RS-BPearl are integrated on 4 sides around the vehicle.

The BPearl is a mechanical type LiDAR based on the same platform as 16/32/Ruby LiDAR but special designed for the blind spot area detection.

 

 

RoboSense’s LiDAR production line recently obtained the IATF16949 Letter of Conformity. This is a huge milestone for the company, can you explain the importance behind this letter and what it means for the company?

IATF 16949 is the most widely used global quality management standard for the automotive industry, which emphasizes various product reliability metrics. RoboSense has obtained the IATF16949 certificate in the automotive field, which now fully qualifies it to supply to automotive customers. It also has accelerated partnerships of automotive-grade LiDAR serial productions with major OEMs and Tier1s. Moreover, it stands for the global industry experts’ recognition of RoboSense product design, development, and production processes and also indicates that RoboSense has achieved a new milestone of complete readiness for serial mass production of automotive LiDARs, including the latest solid-state smart LiDAR “RS-LiDAR-M1”.

 

Robosense won this year’s CES 2020 innovation award for the first MEMS-based smart LiDAR sensor, the RS-LiDAR-M1. What sets it apart from competing solutions?

Since opening to partners in 2017, the Smart LiDAR Sensor’s built-in perception algorithm, the RS-LiDAR-Algorithm, is in the leading position in the automotive LiDAR industry. The RoboSense RS-LiDAR-M1 Smart LiDAR is world’s first and smallest MEMS-based smart LiDAR sensor incorporating LiDAR sensors, AI algorithms and IC chipsets, which transforms overpriced traditional LiDAR systems (also known as solely information collectors) to full data analysis and comprehension system, providing rich and reliable 3D point cloud data and structured, semantic environmental perception results in real-time for a faster autonomous vehicle decision-making than ever before. It fully ensures Level 3-Level 5 advanced automatic driving with the highest level ASIL-D relevant perception safety, which distinguishes us a lot from LiDAR companies.

“The RoboSense RS-LiDAR-M1 Smart LiDAR is world’s first and smallest MEMS-based smart LiDAR sensor”

In addition, the RS-LiDAR-M1 based on solid-state MEMS technology meets the automotive requirement. The RS-LiDAR-M1 has a field of view of 120°*25°, which is the MEMS solid-state LiDAR’s largest field of view among released products worldwide. RoboSense uses 905nm lasers with low cost, automotive grade and small size instead of expensive 1550nm lasers.

 

How does the LiDAR industry in China compared to North America?

LiDAR industry in China starts later than North America, but sooner becomes one of the fastest-growing markets in terms of autonomous driving. In 2018, RoboSense won a strategic investment of over $45 million USD from Alibaba Cainiao Network, SAIC and BAIC, setting the largest single financing record in China's LiDAR industry. Along with this strategic investment, powered by RoboSense’s MEMS Solid-State LiDAR M1, Alibaba Cainiao announced the UAV logistic vehicle which accelerates the LiDAR application in the logistic market. Meanwhile, the RoboTaxi application also speeds up the LiDAR market in China since last year.

As a conclusion, the current market size in China is smaller than the US, but I do also see the fast growth in application of autonomous driving, MaaS, logistics, and robot applications.

 

When do you believe that we will see fully operation Level 5 autonomous vehicles on the road?

Fully automated vehicles (L5) to see on the road, I think, will still take a long time to be reached. There will be step-by-step growth in autonomous vehicles. There are already vehicles equipped with L3 system. Also, some of our partners and customers are in developing the L4 system with a potential start of production time in 5 years. But for the fully automated L5 vehicle, the biggest concerns are always the safety and public acceptance. If they are not able to prove that fully automated vehicles are safer than human drivers, there will be difficulty becoming popular. Currently, I do see the industry is moving in this direction step by step. But I don’t think there will be fully automated vehicles in 10 years.

 

Is there anything else that you would like to share about Robosense? 

RoboSense has received numerous awards, including the CES 2020 and 2019 Innovation Awards, 2019 AutoSens Award, and 2019 Stevie Gold Award and our partners cover the world’s major autonomous driving technology companies, OEMs, and Tier 1s, including the world’s leading automaker, China’s FAW(First Automobile Works), who will use the RoboSense RS-LiDAR-M1 LiDAR as FAW’s proprietary next-generation autonomous driving system.

RoboSense will focus on the development of the solid-state M1 product into automotive-grade mass-production as the first priority. We are not only developing the hardware, but also software as a comprehensive smart sensor system. The delivery of our Automotive Grade MEMS LiDAR in 2020 was one of our biggest milestones.

In addition, safety is the biggest challenge we will tackle. To ensure safety, fusion with different sensors is needed. Furthermore, an AD-friendly infrastructure, such as an intelligent vehicle cooperative infrastructure system (IVICS), also supports autonomous driving. Therefore, the development of short-range Blind Spot Detection (BSD) LiDAR, multiple sensor fusion projects and IVICS projects to provide high precision perception systems are also our focus in 2020.

Thank you for this fascinating interview, anyone who wishes to learn more should visit Robosense.