Technical Walkthrough 3

Detecting Objects in Point Clouds Using ROS 2 and TAO-PointPillars

Accurate, fast object detection is an important task in robotic navigation and collision avoidance. Autonomous agents need a clear map of their surroundings to... 6 MIN READ
Technical Walkthrough 1

Detecting Objects in Point Clouds with NVIDIA CUDA-Pointpillars

A point cloud is a data set of points in a coordinate system. Points contain a wealth of information, including three-dimensional coordinates X, Y, Z; color;... 4 MIN READ
News 0

Webinar: Learn How NVIDIA DriveWorks Gets to the Point with Lidar Sensor Processing

With NVIDIA DriveWorks SDK, autonomous vehicles can bring their understanding of the world to a new dimension. The SDK enables autonomous vehicle developers to... 2 MIN READ
Technical Walkthrough 1

Accelerating Lidar for Robotics with NVIDIA CUDA-based PCL

Many Jetson users choose lidars as their major sensors for localization and perception in autonomous solutions. Lidars describe the spatial environment around... 7 MIN READ
Technical Walkthrough 0

Autonomous Vehicle Radar Perception in 360 Degrees

Our radar perception pipeline delivers 360-degree surround perception around the vehicle, using production-grade radar sensors operating at the 77GHz automotive... 11 MIN READ
Technical Walkthrough 0

Point Cloud Processing with NVIDIA DriveWorks SDK

The NVIDIA DriveWorks SDK contains a collection of CUDA-based low level point cloud processing modules optimized for NVIDIA DRIVE AGX platforms. The DriveWorks... 8 MIN READ