Many people will play games, so do you know ADI? Gamers perform various actions with bare hands in front of the game equipment, and easily play game roles in various virtual worlds; robots of various colors navigate autonomously in various scenes, easily avoiding The obstacle can move quickly to achieve a variety of specific target tasks such as autonomous cleaning, express delivery or inspection; when the truck driver is drowsy in the afternoon, he stops the car to rest under the constant warning sound from the cockpit to ensure safety… These are all There are more and more realistic technology application scenarios in our lives, and ToF (Time of Flight) is becoming one of the key enabling technologies for these many innovative applications.
ToF has quickly entered the public eye from the initial trend application of mobile phone cameras, and has begun to show greatness in various application fields. According to the IHS Markit report, based on the multi-faceted advantages of the ToF solution, the ToF market is expected to reach US$1.5 billion in 2022, accounting for about 50% of the 3D sensing market. In a recent interview with the media, ADI Industrial Marketing Manager Li Jia also believed that, as one of the three mainstream solutions in the field of 3D depth vision, ToF technology is not only used in mobile phones, but also in VR/AR gesture interaction, automotive Electronic ADAS, Security monitoring and new retail have begun to show their talents, which is expected to promote a new wave of 3D intelligent perception application innovation.
The booming ecology promotes a new wave of 3D intelligent perception applications of ToF technology
As we all know, the biggest advantage of ToF in comparison with binocular and structured light is ranging. Its depth calculation accuracy often does not change with distance, and it can basically be maintained at the centimeter level. Therefore, the applicability of ToF is very high in scenarios involving a large range of motion. Before 2010, ToF technology was mostly used in scientific research fields such as cosmology and high-precision microscopes. With the substantial improvement in the performance of light-emitting components, industries such as autonomous driving, VR/AR, industrial robots, and the Internet of Things have gradually emerged, further driving ToF. Application market development. “At present, the application scenarios with the highest degree of ToF matching include ranging and perception of the driving environment in autonomous driving, monitoring of safe distances for human-machine collaboration in the industrial field, machine vision, volume and computing in the logistics industry, and robot navigation, etc. , all make full use of the advantages of ToF sensors in precise positioning and distance measurement.” Li Jia pointed out.
Pulsed ToF is one of those depth-of-field measurement techniques. In order to precisely synchronize light pulses, these calculations need to be performed on millions of pixels per second, and also adjusted for operating conditions, which is extremely important for mixed-signal circuit design and applications. Challenging, ADI is one of the few companies with the technical expertise to provide ToF solutions that are both high-performance and cost-effective. In 2014, ADI began to customize ToF technology for a well-known foreign AR glasses, which successfully landed and realized human-computer interaction and 3D reconstruction functions; 2016-2017, ADI ToF technology was used for in-vehicle gesture recognition; 2018, ADI ToF The technology began to cooperate with a domestic brand of mobile phones and successfully launched in batches… “So far, ADI’s ToF technology and products not only cover industries, consumption, automobiles, etc., but the boundaries of applications continue to expand. In the future, there will be more space and more The combination of high-resolution depth data with powerful classification algorithms and AI will unlock more new scenarios,” Li Jia said.
In the past period of time, ToF applications have gradually shown a trend of accelerating the landing. For example, SLAM (Synchronous Positioning and Mapping) has begun to play an active role in the autonomous positioning and navigation of robots, effectively promoting the realization of human-computer interaction; the ToF module developed by ADI combines image sensors and VGA ToF sensor modules with built-in images The processor solution provides a wider range of collision detection and prevention for applications such as car reversing systems, door opening protection systems, parking assist systems and blind spot detection. “To further improve the large-scale application of ToF technology in the industry, it is always necessary to cooperate with partners in the upstream, midstream and downstream industry chains, including optics, electricity, chip level, circuit level, and module factories, etc., and even some applications require professional teams. Develop and adapt the entire solution.” Li Jia pointed out. It is reported that ADI has launched a 3D time-of-flight development kit with Arrow, and has cooperated with a number of software solution companies such as Envision Intelligence to launch a complete solution that meets rich application scenarios.
ADI ToF analog front-end core chip analysis, building an accurate measurement hardware platform
Generally speaking, ToF technology can be divided into two types according to different modulation methods: pulse modulation and continuous wave modulation. Both ToF modulation methods have their own advantages and disadvantages. Points that need to be comprehensively considered according to the actual application use case include the measurement distance, the environment in which the system is used, accuracy requirements, thermal/power constraints, form factor, and power issues. According to Li Jia, ADI’s ToF solution currently mainly adopts the pulse principle of CCD sensor. As a global exposure device, CCD has very good performance in outdoor long-distance scenes. At the same time, CCD is used as a sensor for global exposure, and it is also a narrow shutter exposure, which has very strong anti-interference performance to the outside world.
Specifically, ADI’s ToF solution uses a high-performance ToF CCD and integrates a 12-bit ADC, a depth processor (which processes raw analog image signals from the CCD into depth/pixel data), and a high-precision clock generator (for CCD and laser generation drive timing) ToF analog processing front-end. The ToF CCD main chip ADDI903x series has good performance. The sensor converts the collected optical signal into an electrical signal, uses depth calculation to send the final distance information to the SOC for processing, and then provides the data to the algorithm for adaptation. The whole process involves sensors and lenses. , launch devices, platforms, applications, etc. For hardware manufacturers, it is necessary to cooperate with module manufacturers to create miniaturized and highly integrated products to adapt to application manufacturers, and then adapt to different application scenarios.
Since the ADI ToF system-level solution uses a ToF image sensor with a resolution of 640×480, its resolution is 4 times higher than that of most other ToF solutions on the market. At the same time, this system-level ToF solution can provide higher system performance in the same size or at the same cost compared to CMOS solutions. For example, high resolution can better distinguish the subject from the background in a complex lighting environment. Thanks to the CCD architecture designed for the 940nm emission band, the ADI ToF solution can also more accurately capture images in motion environments.
In addition to front-end chips and sensors, more optoelectronic devices will be required according to the needs of CCDs, and the peripheral devices of ADI’s ToF solution are all products of ADI. “The ADI ToF system-level solution is not recommended for customers to make too many modifications during use, because each module in the system is the best overall performance state of the system that ADI has long-term and partners to achieve.” Li Jia emphasized in particular road.
Find and solve potential technical pain points, and explore broader paths for ToF applications
More and more application scenarios have opened up one outlet after another for ToF, but related challenges may also arise, such as how to avoid interference between multiple ToF application terminals in the same scenario, especially for professionals such as automobiles and industries. For high-level scenarios, the design of ToF sensing systems not only needs to strike a balance between accuracy, range, response time, resolution, cost, power consumption, and available packaging requirements, but also needs to address various uncontrollable factors, make some customized designs for the flexibility and anti-interference of the sensing system, such as adding some high-reliability filtering and anti-jamming devices and modules, and loading related software algorithms to ensure that the system has sufficient Ability to deal with different types of emergencies.
Just imagine if multiple autonomous robots are sorting goods in the same large warehouse, or if two autonomous vehicles are approaching an intersection at the same time, and the ToF cameras cannot eliminate the interference of mutual light sources, then the application range of accurate depth measurement using ToF technology will be. Severely limited (ADI development roadmap is expected to achieve 64 cameras for simultaneous proximity detection scenarios). Even on the consumer side, with the increase of various applications, the interference between devices will also be a real and practical problem. Therefore, ADI believes that the ability to prevent or eliminate interference in ToF systems will become increasingly important. According to reports, ADI currently uses a patent-pending algorithm that avoids or eliminates all irrelevant light information and uses only the light information of its own laser source, so it can give correct depth information. The deep processor adopts pseudo-randomization algorithm and special image processing function, which can eliminate multi-machine interference. Therefore, multiple ADI ToF systems can be used in the same environment.
In addition, as 3D algorithms become more mature, data analysis will be used to collect a lot of useful information about people’s behavior, and this technology may first be used in building control applications such as access control systems. Vertically mounted sensors add depth information, which means people can be counted very accurately. Another use case is smart automatic door opening, which can differentiate between people and only open when a real person is detected. ADI is also currently developing software algorithms for people counting and human-human differentiation, which, by using depth information, can classify people with high accuracy in many challenging conditions, such as in dimly lit or no ambient light, in populations In denser areas, and in situations where personnel dress is complicated. Best of all, people counting errors are virtually eliminated.
Summary of this article
For many technologies, the maturity of the technology is not the only factor for the popularization of the technology, but also has a great relationship with the cost of the technology and the coordination of the industry chain. In the past 2019, ToF technology has been widely adopted by leading mobile phone manufacturers, and has taken a key step in the evolution of technology.
In the future, how to achieve a balance in terms of cost, power consumption, volume, speed, life, stability, and anti-interference ability through technical means to achieve a more optimized level than the present, and then realize the practical application of ToF technology. The exponential increase in reliability is the premise for the popularization of ToF technology and the healthy development of the entire market, and it is also the research focus that ToF technology system-level solution providers such as ADI need to consider. The above is the ADI ToF high-performance development platform, and the relevant technical analysis of ADI’s innovative application landing scenarios. I hope it can help you.