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lidar_fake_perception package from autoware_learn repo

amathutils_lib autoware_build_flags autoware_health_checker emergency_handler gnss lanelet2_extension libvectormap libwaypoint_follower map_file object_map op_planner op_ros_helpers op_simu op_utility ros_observer tvm_utility vector_map vector_map_server vehicle_sim_model autoware_connector ekf_localizer gnss_localizer image_processor imm_ukf_pda_track lidar_apollo_cnn_seg_detect lidar_euclidean_cluster_detect lidar_fake_perception lidar_kf_contour_track lidar_localizer lidar_naive_l_shape_detect lidar_point_pillars lidar_shape_estimation naive_motion_predict ndt_cpu ndt_gpu ndt_tku obj_db pcl_omp_registration pixel_cloud_fusion points_downsampler points_preprocessor pos_db range_vision_fusion road_occupancy_processor roi_object_filter trafficlight_recognizer twist_generator vel_pose_diff_checker vision_beyond_track vision_darknet_detect vision_lane_detect vision_segment_enet_detect vision_ssd_detect astar_search costmap_generator decision_maker dp_planner ff_waypoint_follower freespace_planner lane_planner lattice_planner ll2_global_planner mpc_follower op_global_planner op_local_planner op_simulation_package op_utilities pure_pursuit state_machine_lib twist_filter twist_gate way_planner waypoint_maker waypoint_planner autoware_quickstart_examples autoware_can_msgs autoware_config_msgs autoware_external_msgs autoware_lanelet2_msgs autoware_map_msgs autoware_msgs autoware_system_msgs tablet_socket_msgs vector_map_msgs carla_autoware_bridge gazebo_camera_description gazebo_imu_description lgsvl_simulator_bridge vehicle_gazebo_simulation_interface vehicle_gazebo_simulation_launcher wf_simulator autoware_bag_tools autoware_camera_lidar_calibrator autoware_launcher autoware_launcher_rviz calibration_publisher data_preprocessor graph_tools kitti_box_publisher kitti_launch kitti_player lanelet_aisan_converter log_tools map_tf_generator map_tools marker_downsampler mqtt_socket multi_lidar_calibrator oculus_socket pc2_downsampler rosbag_controller runtime_manager sound_player system_monitor tablet_socket twist2odom udon_socket vehicle_engage_panel vehicle_socket decision_maker_panel detected_objects_visualizer fastvirtualscan gazebo_world_description glviewer integrated_viewer points2image rosinterface autoware_rviz_plugins vehicle_description vehicle_model adi_driver as autoware_driveworks_gmsl_interface autoware_driveworks_interface vlg22c_cam custom_msgs garmin hokuyo javad_navsat_driver kvaser sick_lms5xx memsic_imu microstrain_driver nmea_navsat autoware_pointgrey_drivers sick_ldmrs_description sick_ldmrs_driver sick_ldmrs_laser sick_ldmrs_msgs sick_ldmrs_tools vectacam xsens_driver ymc ds4 ds4_driver ds4_msgs lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation mrt_cmake_modules

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Package Summary

Tags	No category tags.
Version	1.12.0
License	Apache 2
Build type	CATKIN
Use	RECOMMENDED

Repository Summary

Description	autoware.ai perf
Checkout URI	https://github.com/is-whale/autoware_learn.git
VCS Type	git
VCS Version	1.14
Last Updated	2025-03-14
Dev Status	UNKNOWN
Released	UNRELEASED
Tags	No category tags.
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Package Description

The lidar_fake_percetion package

Additional Links

No additional links.

Maintainers

Akihito Ohsato

Authors

Akihito Ohsato

autoware/core_perception/lidar_fake_perception/README.md

Lidar fake perception

This node generates fake object and pointcloud message based on the value given manually. At the sametime, real pointclouds and real detected objects can be merged as sources.

How to launch

From Runtime Manager:

Computing -> Detection -> lidar_detector -> lidar_fake_perception

From CLI:

$ roslaunch lidar_fake_perception lidar_fake_perception.launch

Parameters

Parameters can be set in both Launch file and Runtime manager:

Parameter in RM	Parameter in Launch	Type	Description	Default
`initial pose`	`initial_pose_topic`	String	Initial fake object pose	`/move_base_simple/goal`
`input objects`	`real_objects_topic`	String	Input objects	`/detected_objects`
`input points`	`real_points_topic`	String	Input points	`/points_raw`
`input twist`	`fake_twist_topic`	String	Input twist command, controlling fake object	`/fake_twist`
`output objects`	`fake_objects_topic`	String	Output objects, input and fake object are merged	`/fake_objects`
`output points`	`fake_points_topic`	String	Output points, input and fake points are merged	`/fake_points`
`publish object`	`publish_objects`	Bool	Enable publishing fake objects	`true`
`publish points`	`publish_points`	Bool	Enable publishing fake points	`true`
`publish rate`	`publish_rate`	Double	Publish rate of fake objects/points [Hz]	`10.0`
`object length`	`object_length`	Double	Length [m]	`4.8`
`object width`	`object_width`	Double	Width [m]	`1.8`
`object height`	`object_height`	Double	Height [m]	`1.8`
`object z offset`	`object_z_offset`	Double	Z Offset from global frame [m]	`0.0`
`use input twist`	`use_fake_twist`	Bool	Using subscribed twist	`false`
`object velocity`	`object_velocity`	Double	Constant velocity instead of subscribed twist [m/s]	`3.0`
`object angular velocity`	`object_angular_velocity`	Double	Constant angular velocity instead of subscribed twist [rad/s]	`0.0`
`object points intensity`	`object_intensity`	Double	Constant intensity value of fake points, 0-255 [-]	`100.0`
`object lifetime`	`object_lifetime`	Double	Fake object lifetime (NOTE: when this is negative value, lifetime is inifinity) [s]	`-1`
`object points space`	`object_points_space`	Double	Fake points space [m]	`0.2`
`output label`	`object_label`	String	Fake object label (e.g. tracking state)	`Stable`
`output frame`	`object_frame`	String	Fake object frame_id (NOTE: not affected to input object)	`velodyne`

Subscriptions/Publications

Node [/lidar_fake_percetion]
Publications:
 * /fake_objects [autoware_msgs/DetectedObjectArray]
 * /fake_points [sensor_msgs/PointCloud2]

Subscriptions:
 * /move_base_simple/goal [geometry_msgs/PoseStamped]
 * /detected_objects [autoware_msgs/DetectedObjectArray]
 * /points_raw [sensor_msgs/PointCloud2]
 * /fake_twist [geometry_msgs/Twist]
 * /tf [tf2_msgs/TFMessage]

CHANGELOG

Changelog for package lidar_fake_perception

1.11.0 (2019-03-21)

[fix] Install commands for all the packages (#1861)
- Initial fixes to detection, sensing, semantics and utils
- fixing wrong filename on install command
- Fixes to install commands
- Hokuyo fix name
- Fix obj db
- Obj db include fixes
- End of final cleaning sweep
- Incorrect command order in runtime manager
- Param tempfile not required by runtime_manager
- - Fixes to runtime manager install commands
- Remove devel directory from catkin, if any
- Updated launch files for robosense
- Updated robosense
- Fix/add missing install (#1977)
- Added launch install to lidar_kf_contour_track
- Added install to op_global_planner
- Added install to way_planner
- Added install to op_local_planner
- Added install to op_simulation_package
- Added install to op_utilities
- Added install to sync
- - Improved installation script for pointgrey packages
- Fixed nodelet error for gmsl cameras
- USe install space in catkin as well
- add install to catkin
- Fix install directives (#1990)
- Fixed installation path
- Fixed params installation path
- Fixed cfg installation path
- Delete cache on colcon_release
Fix license notice in corresponding package.xml
Contributors: Abraham Monrroy Cano, amc-nu

1.10.0 (2019-01-17)

Fixes for catkin_make
Use colcon as the build tool (#1704)
- Switch to colcon as the build tool instead of catkin
- Added cmake-target
- Added note about the second colcon call
- Added warning about catkin* scripts being deprecated
- Fix COLCON_OPTS
- Added install targets
- Update Docker image tags
- Message packages fixes
- Fix missing dependency
Feature/perception visualization cleanup (#1648)
- - Initial commit for visualization package
- Removal of all visualization messages from perception nodes
- Visualization dependency removal
- Launch file modification
- - Fixes to visualization
- Error on Clustering CPU
- Reduce verbosity on markers

File truncated at 100 lines see the full file

Package Dependencies

Deps	Name
	autoware_build_flags
	catkin
	autoware_msgs
	geometry_msgs
	pcl_ros
	roscpp
	sensor_msgs
	tf
	tf_conversions

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

launch/lidar_fake_perception.launch
- - initial_pose_topic [default: /move_base_simple/goal]
  - real_objects_topic [default: /detected_objects]
  - real_points_topic [default: /points_raw]
  - fake_twist_topic [default: /fake_twist]
  - fake_objects_topic [default: /fake_objects]
  - fake_points_topic [default: /fake_points]
  - publish_objects [default: true]
  - publish_points [default: true]
  - publish_rate [default: 10.0]
  - object_length [default: 4.8]
  - object_width [default: 1.8]
  - object_height [default: 1.8]
  - object_z_offset [default: 0.0]
  - use_fake_twist [default: false]
  - object_velocity [default: 3.0]
  - object_angular_velocity [default: 0.0]
  - object_intensity [default: 100.0]
  - object_lifetime [default: -1]
  - object_points_space [default: 0.2]
  - object_label [default: Stable]
  - object_frame [default: velodyne]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

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