3D Modeling AI Autonomous vehicles Laser Scanning Lidar Technology

Autonomous Lidar System Design – Classify or Detect?

graphic of Autonomous Lidar Design Issues
Autonomous Lidar Design Issues

The promise of a fully autonomous tomorrow no longer seems like a pipe dream. Today, the questions around autonomy center on the underlying technologies and the advancements needed to make autonomy a reality. Light detection and ranging (LIDAR) has become one of the most discussed technologies supporting the shift to autonomous lidar applications, but many questions remain. LIDAR systems with ranges greater than 100 m and 0.1° of angular resolution continue to dominate autonomous driving technology headlines.

From an article in Embedded Computing Design by Sarven Ipek and Ron Kapusta.

However, not all autonomous applications require this level of performance. Applications such as valet park assist and street sweeping are two such examples. There are plenty of depth sensing technologies that enable these applications, such as radio detection and ranging (radar), stereo vision, ultrasonic detection and ranging, and LIDAR. However, each of these sensors has a unique trade-off between performance, form factor, and cost. Ultrasonic devices are the most affordable, but are limited in range, resolution, and dependability. Radar is much improved in range and dependability, but it also has angular resolution limitations, while stereo vision can have a large computational overhead and limitations in accuracy, if not calibrated properly. Thoughtful LIDAR system design helps bridge these gaps with precision depth sensing, fine angular resolution, and low complexity processing, even at long ranges. However, LIDAR systems are typically viewed as bulky and costly, which needn’t be the case.

LIDAR system design begins with identifying the smallest object the system needs to detect, the reflectivity of that object, and how far away that object is positioned. This will define the system’s angular resolution. From that, the minimum achievable signal-to-noise ratio (SNR) can be calculated, which is the true/false positive or negative detection criteria needed to detect the object.

For the complete article CLICK HERE.

Note – If you liked this post click here to stay informed of all of the 3D laser scanning, geomatics, UAS, autonomous vehicle, Lidar News and more. If you have an informative 3D video that you would like us to promote, please forward to editor@lidarnews.com and if you would like to join the Younger Geospatial Professional movement click here.


1 Comment


    To LiDAR News,
    To Whom It May Concern,

    I came across your website and thought that you may be looking for a high skilled, professional and good value partner to support you in converting Pointclouds to BIM, the work requires experience, carefulness and patience to produce 3D BIM Models accurately. So I would like to take this opportunity to introduce our team.

    We, BIM Solutions Viet Nam JSC (https://bimsolutions.vn/), an Engineering solutions provider. We are a one-stop multi-disciplinary support service organization providing, Architecture, BIM, Steel & Structure, MEP and especially Pointclouds to BIM for surveying companies. We have global experience on vast of the projects, experience working with survey companies. So that, I think we can be a potential partner for your company in the time to come.

    If you are interested in our services, please leave us a message so we can discuss further on it.
    Thank you so much and looking forward to hearing from you soon.

    Best Regards

    Cam Tu – Business Development Team
    BIM Solutions Viet Nam JSC
    Tel +84-584.238.245
    Email: camtu@bimsolutions.vn

Leave a Comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: