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What is VrLiDAR?

The goal remains consistent: to extract valuable insights from images and point cloud data sources such as LiDAR and Digital Surface Models (DSM), converting them into vectors and attributes usable in various industries. VrThree (VrLiDAR) enables photogrammetry firms to maximize the potential of their existing teams and software while also providing cutting-edge and effective solutions for diverse mapping disciplines, including architecture, engineering, and surveying. This software effortlessly integrates point cloud information into the established Vr Mapping Software suites, VrOne® and VrTwo, making it easier to visualize and edit LiDAR point data in both 2D and realistic three-dimensional stereo formats. The four configurations available in VrThree support the collection and modification of vector, symbol, and text entities using the extensive tools offered by VrOne® and VrTwo. In today's landscape, mapping professionals are tasked with acquiring three-dimensional vector data not only through traditional photogrammetric techniques but also through sophisticated technologies like LiDAR, thereby broadening their skill set. As mapping technology progresses, it continuously prompts experts to adapt and refine their abilities to fulfill the evolving requirements of contemporary projects, ensuring they remain competitive in a rapidly changing environment.

What is NVIDIA DRIVE Map?

NVIDIA DRIVE® Map is a sophisticated mapping solution specifically designed to bolster vehicle autonomy while prioritizing safety. It combines accurate ground truth mapping with the nimbleness and extensiveness of AI-powered fleet-generated mapping, yielding impressive outcomes. The platform incorporates four unique localization layers—camera, lidar, radar, and GNSS—offering essential redundancy and adaptability for advanced AI-driven systems. Emphasizing unparalleled accuracy, the ground truth map engine creates DRIVE Maps by synthesizing data from various sensors, such as cameras, radars, lidars, and differential GNSS/IMU, all collected via NVIDIA DRIVE Hyperion data collection vehicles. It achieves remarkable precision of under 5 cm, especially in high autonomy contexts (L3/L4), in settings like urban landscapes and highways. Tailored for swift performance and global compatibility, DRIVE Map takes advantage of both ground truth and fleet-generated data, representing the collective intelligence of millions of vehicles on the road. This cutting-edge methodology not only improves mapping accuracy but also plays a vital role in advancing the future of autonomous driving technology, paving the way for safer roadways and smarter transport systems.

Media

Media

Integrations Supported

Baidu
Simulink

Integrations Supported

Baidu
Simulink

API Availability

Has API

API Availability

Has API

Pricing Information

$2500.00/one-time/user
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Cardinal Systems

Company Website

www.cardinalsystems1.net/vrlidar

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

www.nvidia.com/en-us/self-driving-cars/hd-mapping/

Categories and Features

CAD

2 1/2-Axis Milling
2D Drawing
3-Axis Milling
3D Modeling
4-Axis Milling
5-Axis Milling
Civil
Collaboration
Database Connectivity
Design Analysis
Design Export
Document Management
Electrical
Hole Making
Mechanical
Mechatronics
Presentation Tools
Simulate Cycles
Spiral Output
Structural Engineering
Toolpath Simulation
User Defined Cycles

Categories and Features

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