AiThority Interview Series with Mark Qiu, Co-Founder and COO, RoboSense

“In the future, RoboSense will also create a LiDAR sensing solution based on MEMS solid-state optical LiDAR that meets the needs of the mass production of autonomous driving vehicles based on mature P3 solutions.”

Know My Company

Tell us about your journey in RoboSense. How did you start the company?

RoboSense was founded in 2014 as a robotic environment sensing system. We primarily focus on autonomous driving LiDAR environment perception, which is a type of sensing system. This strategy is also fully in line with our initial direction. RoboSense has had more than ten years of research and development in the field of robotic environment perception. For me, autonomous driving is the robotics technology of cars, which needs environmental perception solutions. That is exactly what we are doing.

When our start-up team began our LiDAR-based perception algorithm research, we realized that LiDAR was not only expensive, but was also an immature technology. In addition, sensing-based algorithms relied, to a large extent, on raw point cloud data produced by the sensor alone, which seriously hindered technology development. The algorithm and hardware needed to be combined together to provide power similar to “eyes.”

Therefore, we began the development of our own LiDAR hardware. In 2015, we first developed a single-laser transmitter that emitted 500,000 points per second, with an accuracy of a 2mm 3D laser scanner and point cloud algorithm software for varied industries. Then, we launched a multi-line LiDAR that met the needs of autonomous driving and brought LiDAR hardware and sensing algorithms to the market, creating a complete LiDAR sensing system for autonomous driving.

With the rapid development of the autonomous driving industry, the requirements for LiDAR have continuously increased. In order to help customers faced with these challenges, we have introduced a revolutionary MEMS solid-state LiDAR, which propels autonomous driving technology into large-scale commercialization.

In 2018, RoboSense entered a more rapid and steady developmental stage for our technology, products, and markets. The RS-LiDAR-M1 Pre, the MEMS solid-state LiDAR, was released last year. It has undergone a half a year of R&D adjustments and technical improvements after the world’s first public demonstration at CES2018 last January. In May 2018, our solid-state LiDAR was loaded on the Cainiao unmanned logistics vehicle, unveiled at the Ali Cainiao Global Intelligent Logistics Conference, thereby becoming the world’s first solid-state LiDAR for unmanned vehicles.

RoboSense has already been shipping our MEMS LiDAR product to the world’s top OEMs and Tier 1 suppliers. At the same time, shipments of the multi-line LiDAR RS-LiDAR-16 and RS-LiDAR-32 have significantly increased after beginning mass production last year, and are widely used in autonomous driving logistics vehicles, buses, passenger cars, drones, unmanned ships, and many other fields.

With regards to our software algorithm, because of RoboSense’s over ten years of R&D, we are the only global provider of high-beam LiDAR hardware and software sensing algorithms. We are able to provide different levels of environment-aware algorithms in various autonomous driving scenarios. As an environment-aware solutions provider of self-driving LiDAR, RoboSense offers a wide range of LiDAR environment-aware solutions for a variety of autonomous driving scenarios based on the most advanced LiDAR hardware and perception algorithms, including the P1 solution for low-speed auto-driving scenarios, the P2 solution for medium to high-speed auto-driving scenarios, and the P3 solution for high-level auto-driving requirements above L3.

In the future, RoboSense will also create a LiDAR sensing solution based on MEMS solid-state optical LiDAR that meets the needs of the mass production of autonomous driving vehicles based on mature P3 solutions.

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In the fast-growing LiDAR ecosystem, how does RoboSense stay on top of competition?

With the development of LiDAR, there is a trend towards competing with each other. RoboSense is the world’s leading provider of LiDAR environment-aware solutions. We have accumulated over ten years of technology knowledge in the field of LiDAR sensing hardware and software algorithms, and we are very market-oriented, providing customers with different options of intelligent environment-aware LiDAR systems.

In terms of hardware, our multi-line LiDAR is fully developed on core features, such as product performance and mass production capability. Our products have been supplied to the automotive market for a long time, and we have a deep understanding of LiDAR technology and the autonomous driving industry as a whole.

Solid-state LiDAR is a next-generation product. Throughout the world, there is only a handful of vendors that can actually produce LiDAR. We have completed test drive verification for RoboSense’s LiDAR Perception Algorithms for two years with hundreds of partners. RoboSense has underlying technological innovations and is market demand-oriented to accelerate the large-scale commercialization of the automotive driving industry.

What are the core tenets of your LiDAR technology?

LiDAR is an indispensable sensor for autonomous driving, enabling safe driving in autonomous vehicles. RoboSense aims to provide a safer, more reliable, higher performance and lower cost LiDAR system solution for autonomous vehicles, helping customers solve the problems of LiDAR environment perception during the commercialization of autonomous driving. 

Tell us more about your recent program – The Autoware Foundation. How do you plan to extend the benefits of this forum to your customers and technology partners?

On December 10, 2018, the Autoware Foundation was officially launched. As an open-source platform, the Foundation has great influence in the industry and has established in-depth cooperation with many top auto-driving companies around the world. We share the same vision with the Autoware Foundation to continuously drive the development of autonomous driving.

We are honored to be a founding industrial member of the Autoware Foundation and we are hoping to contribute to the Autoware Foundation by providing LiDAR hardware and algorithm software that will enable us to build on our deep understanding of LiDAR technology and the autonomous driving industry.

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How do you prepare for the autonomous driving industry powered by Connected Devices, IoT and AI?

In recent years, with the rapid development of Artificial Intelligence, LiDAR, and semiconductor technologies,the industrialization of autonomous driving technology, which had been hidden in the laboratory for the past few decades, has burgeoned. When fully automatic driving arrives,vehicles will have LiDAR with centimeter-level accuracy to sense three-dimensional environmental road conditions, coupled with Artificial Intelligence knowledge equal to a world traveler’s. Autonomous vehicles and road conditions will be easily handled by the cloud, so traffic jam problems can be avoided for optimal road use.

To achieve this, we will continuously make technological innovation and product performance advancements in the creation of a more intelligent LiDAR environment-aware system solution, and continue to provide a smarter, more stable, safer, and lower-cost intelligent LiDAR product. We will solve the problem of LiDAR environment perception during the process of auto-driving commercialization, and further contribute to the development of the autonomous driving industry.

How is the LiDAR industry in China different from other matured regions, including Western Europe and North America?

First of all, the competition of autonomous driving LiDAR, in terms of talent, R&D, manufacturing and market, is global. China’s LiDAR products have gradually emerged in an international context in the past couple of years. LiDAR had previously been produced predominately by non-Chinese companies for a long time. This was because the demand for LiDAR was not clear, and the industry was not mature. However, in recent years, with a now clear demand for LiDAR for autonomous driving, R&D teams have mastered core LiDAR technology and have established many excellent LiDAR companies in China.

As a Chinese LiDAR company, RoboSense entered the industry in 2016 when faced with pressure. The pressure did not come from competitors, but from the discrepancy between market demand and capacity. The autonomous driving industry was driven by capacity demands, which only allowed a few players to exist, since products were in such short supply. Thus, the biggest pressure was how to improve the quality and productivity of our products.

At this stage, the challenge inhibiting the mass production of solid-state LiDAR vehicles is the need to provide automotive grade products that follow strict requirements. For mass production, it is necessary to continuously improve the quality and performance of the products to fit the growing demands of automatic driving. The best way to truly address these pressures is to make products that meet the market’s needs for safety, reliability, high performance, low cost, easy mass production, maturity, and compact size. RoboSense MEMS solid-state LiDAR, the RS-LiDAR-M1, which was exhibited at CES 2019, is the solution that meets all these market needs.

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What are the challenges in making LiDAR a more readily adaptable technology by 2020?

By 2020, the autonomous driving industry will enter a commercial stage, and all autonomous driving producers will be fully competing. The market for self-driving vehicles will boom. At this stage, all types of self-driving vehicles will begin mass production and will be placed into normal operation in various scenarios. LiDAR has strict requirements, such as automotive grade, mass production, high resolution, and low cost. The development trend of LiDAR needs to drive towards mass production, low cost, and high stability.

At present, traditional LiDAR systems are limited by physical limits and high cost, making it difficult to meet the industry’s development needs. Therefore, to realize the large-scale commercial operation for autonomous driving, a new generation of high-precision 3D environment sensing solid-state LiDAR technology products will be required.

Solid-state LiDAR technology solutions are divided into three categories: MEMS, OPA and Flash. These three solutions have different advantages and disadvantages based on their technical principles. Compared to OPA, thousand-yuan (approximately $150 USD) MEMS solutions are pricey and technically not easy to be reduced to hundred-yuan level (approximately $15 USD) in a short time.

On the other hand, MEMS’s strength is its unparalleled ability to detect long-distant objects. There is still a very long way to go for OPA and Flash to achieve 200-meter measurement and detection, which MEMs can already do now.

Faced with technical competition, the core technology of the new generation of products has been mastered by the industry’s rising stars, and the future market will be diversified. At present, the top LiDAR manufacturers that have completed solid-state LiDAR demonstrations are working on achieving vehicle-level test certification, performance improvement, and mass production prep. RoboSense hopes to lower production costs of MEMS solid-state LiDAR to less than $200 USD by 2020.

How do Automation and Big Data come together at Robosense?

For automatic driving technology, Big Data not only brings more convenience but also makes driving safer. Without Big Data, unmanned cars will be difficult to operate. RoboSense will continuously generate sophisticated algorithms based on a large number of real-world scenario and virtual environment simulation testing to improve the perceptual accuracy and the accuracy of LiDAR in general, ensuring autonomous driving instantly responds to complex driving environments.

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Elaborate on your playbook for company-customer interaction. What challenges do traditional communication platforms pose to modern CX teams?

As a provider of autonomous driving LiDAR environment-aware solutions, our customers are fast-growing companies in the autonomous driving industry, where we all face lots of unprecedented challenges. To accelerate the development of autopilot projects and the collection of customer feedback, RoboSense has built a complete and efficient pre-sales and post-sales team to quickly communicate and solve customer problems, while optimizing the product based on feedback, continuously improving our customer experience and product service.

Where do you see the LiDAR market in the next five years? What role do you see for RoboSense in making LiDAR a ready-made platform for automotive businesses?

In 2018, Level 3 to Level 5 autonomous vehicles that must use LiDAR will gradually become an industry standard. Recently, both Audi’s A8, a Level 3 mass produced autonomous vehicle, and Waymo One, an autopilot ride-hailing service, have used LiDAR, which is an important industry signal. High-line LiDAR, such as MEMShigh-resolution, high-stability, low-cost LiDAR, has passed automotive grade testing and is preparing for high-speed mass production. This year, manufacturers with advanced LiDAR technology solutions have started to cooperate with OEMs, and manufacturers that cannot remove mechanical radar solutions are likely to fall behind.

In the next five years, mature mass-produced automotive-grade solid-state LiDAR will become the protagonist of the LiDAR market. We expect that MEMS LiDAR will be the first generation solid-state LiDAR for autonomous driving vehicles, including the RS-LiDAR-M1 MEMS solid-state LiDAR, which was exhibited at CES 2019 by RoboSense.

RoboSense has always been positioned as a provider of self-driving environment-aware LiDAR solutions. We not only provide excellent LiDAR hardware, but also the most advanced LiDAR environment-aware algorithm, providing a software and hardware integrated system solution for all autonomous driving partners to quickly gain unparalleled environmental awareness of the LiDAR system. 

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The Crystal Gaze

What LiDAR & AI start-ups and labs are you keenly following?

We hope that this industry will rapidly develop. We pay attention to major LiDAR companies, for example, Valeo, whose LiDAR has passed automotive grade testing and has been loaded on mass-produced autonomous vehicles, where, in the future, our MEMS will also be loaded. Their precedents are worth learning. In addition,Velodynehas been in the market for over ten years.

They have deep insights into the LiDAR market, so we have also been watching their movements.We also pay attention to AI start-ups and laboratories in the autonomous driving field, including major autonomous driving companies, and Tier one companies — initiators of the LiDAR market demand. As a LiDAR system solution provider, we have always been kept an eye on Tier one companies’ demands in order to continuously optimize and update our LiDAR solutions. 

What technologies within AI and computing are you interested in?

RoboSense provides autonomous driving environment-aware LiDAR solution with two components. The first component is the LiDAR hardware and the second component is AI environment-aware algorithms based on LiDAR point cloud data. We pay more attention to computing and other related technologies for deep learning and parallels in AI and computing. We are committed to exploring the unlimited potential of LiDAR hardware in terms of environment perception through advanced LiDAR sensing algorithms.

As an AI leader, what industries do you think would be the fastest in adopting AI/ML with smooth efficiency? What are the new emerging markets for AI technology markets?

Artificial Intelligence will bring tremendous changes and upgrades to almost every industry. From manufacturing to the service industry, AI is being rapidly commercialized in various fields. Autonomous driving is the best example. Artificial intelligence is literally transforming a trillion-dollar automobile industry, rapidly changing parts suppliers, autonomous driving solutions providers, autopilot service providers, automobile manufacturers, and other traditional enterprises, affecting the entire industrial chain with the rapid development of start-ups.

What’s your smartest work-related shortcut or productivity hack?

To me personally, number one is project and time management, number two is appropriate tools and the right people, and number three is to focus on one thing at a time instead of all over the place.

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Tag the one person in the industry whose answers to these questions you would love to read:

CEO of Waymo, John Krafcik.

Thank you, Mark! That was fun and hope to see you back on AiThority soon.