cuda-organized-pointcloud-adapter.md

cuda_organized_pointcloud_adapter

Purpose

The node cuda_pointcloud_preprocessor expects a 2D pointcloud where every row represents a single channel/ring and each row's points are in non decreasing azimuth order.

To utilize the previously mentioned node, this node provides an adapter to convert standard flat pointclouds (height equals to 1) to the required 2D tensor.

In addition, this node uses the cuda_blackboard, a cuda transport layer that enables a zero-copy mechanism between GPU and GPU memory for both input and output.

Inner-workings / Algorithms

To create the required 2D tensor, this node iterates the input pointcloud sequentially, filling the output 2D tensor depending on the input point's channel.

The output tensor's size is also estimated in this node, based on the largest channel value and the maximum number of points per channel observed so far.

Inputs / Outputs

Input

Name	Type	Description
~/input/pointcloud	sensor_msgs::msg::PointCloud2	Input pointcloud's topic.

Output

Name	Type	Description
~/output/pointcloud	sensor_msgs::msg::PointCloud2	Processed pointcloud's topic
~/output/pointcloud/cuda	negotiated_interfaces/msg/NegotiatedTopicsInfo	Processed pointcloud's negotiation topic

Parameters

Core Parameters

{{ json_to_markdown("sensing/autoware_cuda_pointcloud_preprocessor/schema/cuda_pointcloud_preprocessor.schema.schema.json") }}

Assumptions / Known limits

• This algorithm assumes that the input points will be in non-decreasing azimuth order (per ring).
• This node expects that the input pointcloud is flat (height equals to 1) and follows the autoware::point_types::PointXYZIRC layout defined in the autoware_point_types package.