<DRACO POINT CLOUD TRANSPORT>

Description

Plugin for ROS package point_cloud_transport, which uses Google Draco compression library for low-bandwidth transportation of PointCloud2 messages.

Dynamic Reconfiguration

The plugin provides dynamic reconfiguration parameters, which can be used to change the compression during runtime.

##Publisher

Encode and Decode Speed

By adjusting the encode_speed and dedode_speed parameters, one can adjust the speed at which the plugin encodes the point cloud. The higher the number, the higher the speed of encoding/decoding, but the worse the compression. For more detailed information, see documentation of Draco.

Encode Method

Auto method decides on the encoding method based on other parameter and should be used as the default method.

KD-tree method forces the encoder to use KD-tree encoding. If an attribute in the point cloud is of type float32, kd-tree encoding requires the attribute to be quantized.

Sequential method forces the encoder to use sequential encoding. Quantization can not be used with sequential encoding. Sequential encoding provides much worse compression than KD-tree, but is faster and keeps the arrangement of points in the point cloud intact. Therefore sequential encoding can be used to encode 2D point clouds such as from Kinect.

Deduplicate

Deduplicate option tells the encoder whether or not to delete duplicate points in the point cloud, allowing for transport of smaller point clouds.

Force Quantization

Force_quantization option forces the use of quantization and hence the KD-tree encoding method.

Quantization of Attribute Types

Quantization_POSITION, Quantization_NORMAL, Quantization_COLOR etc. tells the encoder how many bits should be used for quantization of given attribute type. Attribute type of point cloud attribute is recognized based on a list of known names:

• "x" - POSITION
• "y" - POSITION
• "z" - POSITION
• "pos" - POSITION
• "position" - POSITION
• "rgb" - COLOR
• "rgba" - COLOR
• "r" - COLOR
• "g" - COLOR
• "b" - COLOR
• "a" - COLOR
• "nx" - NORMAL
• "ny" - NORMAL
• "nz" - NORMAL
• all others are encoded as GENERIC

To specify custom quantization, one can either edit the list of recognized names or use expert_quantization and expert_attribute_type options.

Expert Quantization

Expert_quantization option tell the encoder to use custom quantization values for point cloud attributes. Multiple POSITION attribute can therefore be encoded with varying quantization levels.

To set a quantization for a PointField entry "x" of point cloud which will be advertised on base topic base_topic, one must set the parameter: /base_topic/draco/attribute_mapping/quantization_bits/x.

Example:

$ rosparam set /base_topic/draco/attribute_mapping/quantization_bits/x 16

When using expert_quantization, user must specify the quantization bits for all PointField entries of point cloud.

Expert Attribute Types

Expert_attribute_types option tell the encoder to use custom attribute types for encoding of point cloud attributes.

To set a type for a PointField entry "x" of point cloud which will be advertised on base topic base_topic, one must set the parameter: /base_topic/draco/attribute_mapping/attribute_type/x.

Example:

$ rosparam set /base_topic/draco/attribute_mapping/attribute_type/x "'POSITION'"

When using expert_attribute_types, user must specify the type for all PointField entries of point cloud. Accepted types are:

• POSITION
• NORMAL
• COLOR
• TEX_COORD
• GENERIC

When encoding rgb/rgba COLOR, user can specify to use the common rgba tweak of ROS (encoding rgba as 4 instances of 1 Byte instead of 1 instance of float32). To inform the encoder, that PointField entry "rgb" should be handled with the tweak, set parameter:

$ rosparam set /base_topic/draco/attribute_mapping/rgba_tweak/rgb true

Subscriber

Set Skip Dequantization of Attribute Types

SkipDequantizationPOSITION, SkipDequantizationNORMAL, SkipDequantizationCOLOR etc. options tell the decoder to skip dequantization of given attribute types.