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What is LidarView?

LidarView, an open-source initiative developed by Kitware, enables users to visualize, record, and process 3D LiDAR data in real-time. Built upon the ParaView framework, this platform excels at rendering large point clouds and includes features such as 3D visualization of time-stamped LiDAR returns, a spreadsheet inspector for various attributes like timestamp and azimuth, and the ability to display multiple data frames simultaneously. It allows for data input from both live sensor streams and recorded .pcap files, giving users the ability to perform 3D transformations on point clouds and manage different subsets of laser data with ease. LidarView supports a wide variety of sensors, including those from well-known manufacturers such as Velodyne, Hesai, Robosense, Livox, and Leishen, enabling the visualization of live data streams or the replay of previously captured information. The platform integrates advanced algorithms for Simultaneous Localization and Mapping (SLAM), facilitating accurate environmental reconstruction and sensor localization. Furthermore, it incorporates AI and machine learning functionalities that improve scene classification, providing users with an extensive toolkit for sophisticated data analysis and visualization. As a result, LidarView stands out as an adaptable solution for both researchers and professionals eager to harness the capabilities of LiDAR technology in their respective fields, ultimately enhancing their project outcomes and insights.

What is Aurora Driver?

Utilizing state-of-the-art hardware and innovative software, the Aurora Driver is designed to fit a variety of vehicle types and applications, allowing us to leverage the benefits of autonomous driving in diverse fields such as long-haul trucking, local parcel delivery, and personal transportation. It is equipped with a comprehensive suite of sensors that collect environmental data, advanced software that determines the safest routes, and a computing system that seamlessly connects both elements with the vehicle. This system is adaptable to various vehicles, ranging from compact automobiles to robust Class 8 trucks, making the Aurora Driver a highly flexible solution. Central to its operation is the Aurora Computer, which acts as the pivotal link between our hardware and autonomous software, facilitating smooth integration across all vehicle models. Our custom-developed sensor ensemble, featuring FirstLight Lidar, long-range imaging radar, and high-definition cameras, works together to generate a detailed three-dimensional representation of the surroundings, granting the Aurora Driver a full 360Ëš awareness in real time. This groundbreaking methodology not only improves safety but also sets the stage for the widespread acceptance of self-driving technology across various transportation sectors. Ultimately, the Aurora Driver represents a significant advancement in the quest to integrate autonomous systems into everyday travel and logistics.

Media

Media

Integrations Supported

Civil Designer
ParaView

Integrations Supported

Civil Designer
ParaView

API Availability

Has API

API Availability

Has API

Pricing Information

Free
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

Kitware

Date Founded

1998

Company Location

United States

Company Website

lidarview.kitware.com

Company Facts

Organization Name

Aurora

Date Founded

2017

Company Location

United States

Company Website

aurora.tech/aurora-driver

Categories and Features

Categories and Features

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