Thursday, 19 July, 2018

Cruise acquires Strobe to help dramatically reduce LiDAR costs

GM Cruise Automation Chevy Bolt Cruise acquires Strobe to help dramatically reduce LiDAR costs
Theresa Hayes | 09 October, 2017, 23:24

"GM's AV's will be ready for commercial deployment, without human drivers, much sooner than widely expected and potentially years ahead of competitors", Deutsche Bank analyst Rod Lache wrote in a September research note. GM and its US rival Ford Motor Co have both publicly stated that they aim to have fully self-driving cars on sale by 2021. (For starters, we don't know the purchase price.) We do know that the deal is done, not pending, and that Strobe's engineering team will join GM's San-Francisco-based self-driving subsidiary, Cruise Automation. There is fierce competition between large automakers to bring autonomous, or self-driving, vehicles to market first.

The particularly attractive thing about Strobe, according to Cruise CEO Kyle Vogt, is that it has successfully reduced the LIDAR array down to a single chip, which will help reduce production costs by almost 100 percent. "When used together, cameras, Lidars, and radars can complement each other to create a robust and fault-tolerant sensing suite that operates in a wide range of environmental and lighting conditions".

Cameras are considered less accurate than Lidar, but these systems can operate in poor weather conditions that confuse Lidars. Most autonomous-vehicle developers use lidar in conjunction with radar and cameras to recognize other vehicles, street signs, pedestrians and other objects. GM's Director of autonomous vehicle integration has recently spoken up against Musk's narrative that Tesla Autopilot will be fully autonomous and capable of piloting a auto from California to NY on its own by the end of the year. "Could you do it with what's in a current Tesla Model S?" The acquisition gives GM exclusive access - and brings GM one step closer to mass-producing self-driving cars. "I don't think so". Existing commercially available solutions cost tens of thousands of dollars, are bulky and mechanically complex, and lack the performance needed to unlock self-driving operation at higher speeds and in more challenging weather.