"Blackmore has unique and innovative FMCW lidar technology that delivers a new dimension of data to future vehicles," said BMW i Ventures partner Zach Barasz. In addition to being more cost-effective, Blackmore's FMCW lidar has several advantages over traditional pulsed lidar systems.
"Blackmore's groundbreaking FMCW lidar technology is designed to eliminate interference, improve long-range performance, and support both range and velocity — a triple threat to make autonomous driving safer," said Jim Adler, managing director of Toyota AI Ventures.
According to Randy Reibel, Blackmore's CEO, it is that last capability that differentiates Blackmore's sensor from its competitors. "Having the ability to measure both the speed and the distance to any object gives self-driving systems more information to navigate safely."
Blackmore will use the investment to scale the production of its FMCW lidar for ADAS and self-driving markets. Increased production capacity will allow Blackmore to support the growing sector of autonomous driving teams demanding a superior lidar solution.
Recent fatal Uber accident shows other sensors but visual camera sensors are useless for automotive applications in most critical situations.
ReplyDeleteAutonomous cars should recognize a person in any harsh environment and no other sensor can replace human-like visual sensor for this purpose. The only way to go is to make super-sensitive, super-fast, and super-resolution visual sensors and make them coupled with super-human visual recognition algorithms.
That kind of solution can replace human perception and that will be enough for sensing.
I agree with you
ReplyDelete"Having the ability to measure both the speed and the distance to any object"
ReplyDeleteDoesn't every ToF system allow to do that by just comparing two measurements (which is essentially what the FMCW approach does as well)
It's not true. ToF system can't provide speed and range at the same frame. The author is talking about FMCW possibility to measure radial velocity and range per each pixel. It significantly reduces the latency, because no need to wait for few frames for the movement analysis. It is especially important at proximity range, as in the case of Arizona accident. Of course, if the camera frame rate and processing time are very fast, which is not the case of Velodyne lidar, situation is different.
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