Oryx Vision Eyes Autonomous Cars

Develops Highly-Accurate Lidar for Self-Driving Vehicles


Lidar is a 3D laser scanning technology originally developed in the 1960s for the military to detect submarines. A lidar system projects laser beam pulses onto a rotating mirror and then collects the light reflected to map the distance between objects in the surrounding area and produce a detailed 3D image. Using the speed of light as a baseline, the system detects the time of flight of the light pulses to gauge how distant objects are. Most lidar systems use light in near-infrared and UV spectrums.

Over time, many technologies tend to trickle down from addressing specific, high-grade enterprise needs to targeting consumers, offering considerably lower prices and different implementations than their predecessors. Lidar has gone from being used in submarine detection, to having a role in the development of autonomous vehicles, an area that will need highly-accurate and cost-effective versions of the technology. Although lidar will be a principal enabler of self-driving cars, other technical approaches are also in the works.

Oryx Vision is one company working to help bring this vision to life. The Israeli innovator of lidar solutions promises what it calls nano-antenna sensors, which perform 50 times better and cost much less than lidar technologies currently on the market. Founded in 2009, the start-up develops solid-state, depth-vision solutions for self-driving cars. Its new sensor uses long-wave infrared lasers to track objects on the roadway. The company claims the technology can see through fog and direct sunlight, environments that other lidar systems currently struggle with. Its microscopic antennas treat the reflected signal as a wave rather than a particle, allowing the sensor to accurately calculate the speed of nearby objects and offer great detail about what it sees.

The company received a boost this week, raising $50 million in a second funding round led by Third Point Ventures and Walden Riverwood Ventures. As lidar is a major way to provide eyesight for self-driving cars, the speed at which the technology develops and its price falls will be a factor in determining how quickly autonomous driving becomes mainstream. Many companies have been racing to innovate in this area given the mass potential of the market. The appropriate lidar systems will need to be able to process detailed imagery at high speeds through heavy traffic and poor weather conditions.

Mega companies such Google and Uber, along with most car-makers, have been looking to perfect the technology, which will, in theory, create an accident-free environment. The first company to do so will have bragging rights as well as a significant revenue stream from licensing intellectual property rights.

We believe that autonomous cars with no human driver will remain a research project until at least 2025 (CCS Insight Predictions for 2017 and Beyond). It's a matter of legislation, regulation, safety and consumer acceptance all lining up. It will take a level of trust in the technology to alter transport behaviours. This will be a big shift.

For now we're excited to see each new step forward. Companies such as Oryx Vision will play crucial roles in driving the concept of autonomous vehicles.

This entry was posted on August 11th, 2017 and is filed under Services. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.

Posted By Raghu Gopal On August 11th, 2017


Comments
(There are no comments yet)
Leave a Comment

Hot News

Team Tweets

CCS Insight
US car-maker @GM seeks to accelerate its self-driving programme by acquiring lidar start-up Strobe: https://t.co/QXcEj4m2v1
Follow CCS Insight
Shaun Collins
RT @LauraSimeonova: Mobile News on CCS Insight's latest Mobile Phone Forecast - https://t.co/OT6kj6LGfw
Follow Shaun
Ben Wood
RT @geoffblaber: Thoughts on Google using #gigabitLTE to help differentiate Android devices https://t.co/4ttBQerUmG
Follow Ben
Martin Garner
@Microsoft + @awscloud collaborate on new deep learning tool, Gluon. https://t.co/XiaefK2k1w. Easier to experiment with neural nets.
Follow Martin
Geoff Blaber
RT @paolopescatore: Another good quarter for Netflix. Higher subs but next quarter could be challenging due to price rises. Content costs o…
Follow Geoff
Marina Koytcheva
Thank you @TriumphUK for helping sort out an annoying situation. I appreciate your quick and effective assistance!
Follow Marina
Nicholas McQuire
Here's a good summary of the AWS & Microsoft #DeepLearning collaboration with our comments from @mobilityxchange https://t.co/nUkGM1m3bV
Follow Nicholas
Paolo Pescatore
Another good quarter for Netflix. Higher subs but next quarter could be challenging due to price rises. Content costs ongoing concern $NFLX
Follow Paolo
Kester Mann
RT @paolopescatore: Light reading ahead of the weekend, my thoughts on forthcoming Premier League rights auction #PL #OTT #video https://t.…
Follow Kester
Laura Simeonova
RT @benwood: Big news from Samsung overnight. Despite strong profits CEO resigns. Cites concerns over future challenges. https://t.co/bqI1…
Follow Laura
Katie Taylor
RT @TheBMA: Two junior doctors were left looking after more than 400 patients during very unsafe shift at stretched hospital https://t.co/q…
Follow Katie

Recent Blog Posts

Blog Post
General Motors to Focus on Autonomous Cars Acquires Strobe, a Lidar Technology Start-Up Fully autonomo... Read more
Blog Post
Web Giants Eye Rights to Football Matches Upcoming Premier League Rights Auction Set to Spark Bidding ... Read more
Blog Post
Project Loon to the Rescue Alphabet Balloons to Offer Emergency Cellular Service in Pue... Read more
More blog

Latest Company News

More news