dummy_perception_publisher

Purpose

This node publishes the result of the dummy detection with the type of perception. The node uses a plugin architecture to support different object movement strategies.

Inner-workings / Algorithms

Plugin Architecture

The node uses a plugin-based architecture to handle different types of object movement. This allows for flexible and extensible movement behaviors without modifying the core node logic.

Available Plugins

1. StraightLineObjectMovementPlugin: Moves objects in straight lines based on their initial velocity and direction.
2. PredictedObjectMovementPlugin: Moves objects along predicted paths from perception predictions, providing more realistic movement patterns.

Plugin Base Class

All movement plugins inherit from DummyObjectMovementBasePlugin which provides:

• Object management (add, delete operations)
• Associated action type handling
• Common interface for object movement

Object Action Handling

• ADD: New objects are created and they move in a straight line, acceleration and deceleration parameters can be used.
• MODIFY: Handled directly by the node, bypassing plugin movement logic. Immediately replaces the object's position information across all plugins.
• DELETE: The specified object is removed from all plugins.
• DELETEALL: Clears all objects from all plugins.
• PREDICT: New objects are created, they move in a straight line for a set time and then the predictions extracted from the perception module are used to dictate where the objects will move to. NOTE: for ease of calculation, acceleration is not taken into account when calculating the object's position, only its initial speed.

Inputs / Outputs

Input

Name	Type	Description
/tf	tf2_msgs/TFMessage	TF (self-pose)
input/object	tier4_simulation_msgs::msg::DummyObject	dummy detection objects
predicted_objects	autoware_perception_msgs::msg::PredictedObjects	predicted objects (used by PredictedObjectMovementPlugin)

Output

Name	Type	Description
output/dynamic_object	tier4_perception_msgs::msg::DetectedObjectsWithFeature	dummy detection objects
output/points_raw	sensor_msgs::msg::PointCloud2	point cloud of objects
output/debug/ground_truth_objects	autoware_perception_msgs::msg::TrackedObjects	ground truth objects

Parameters

Core Parameters

Name	Type	Default Value	Explanation
visible_range	double	100.0	sensor visible range [m]
detection_successful_rate	double	0.8	sensor detection rate. (min) 0.0 - 1.0(max)
enable_ray_tracing	bool	true	if True, use ray tracking
use_object_recognition	bool	true	if True, publish objects topic
use_base_link_z	bool	true	if True, node uses z coordinate of ego base_link
publish_ground_truth	bool	false	if True, publish ground truth objects
use_fixed_random_seed	bool	false	if True, use fixed random seed
random_seed	int	0	random seed
object_centric_pointcloud	bool	false	if True, generate object-centric point clouds
angle_increment	double	0.004363323	angle increment for ray tracing (0.25° in radians)

PredictedObjectMovementPlugin Parameters

Name	Type	Default Value	Explanation
min_predicted_path_keep_duration	double	3.0	minimum time (seconds) to keep using same prediction
switch_time_threshold	double	2.0	time threshold (seconds) to switch from straight-line to predicted path

Common Remapping Parameters

The plugin uses CommonParameters for both vehicle and pedestrian object types. Each parameter is prefixed with either vehicle. or pedestrian.:

Parameter Name	Type	Explanation
max_remapping_distance	double	maximum distance (meters) for remapping validation
max_speed_difference_ratio	double	maximum speed difference ratio tolerance
min_speed_ratio	double	minimum speed ratio relative to dummy object speed
max_speed_ratio	double	maximum speed ratio relative to dummy object speed
speed_check_threshold	double	speed threshold (m/s) above which speed checks apply
path_selection_strategy	string	path selection strategy: "highest_confidence" or "random"