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autoware_freespace_planning_algorithms package from autoware_universe repo

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autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_control_evaluator autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter tier4_autoware_api_launch tier4_control_launch tier4_localization_launch tier4_map_launch tier4_perception_launch tier4_planning_launch tier4_sensing_launch tier4_simulator_launch tier4_system_launch tier4_vehicle_launch autoware_geo_pose_projector autoware_gyro_odometer autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_ndt_scan_matcher autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_initializer autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_lanelet2_map_visualizer autoware_map_height_fitter autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_range_splitter autoware_object_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_crossing_objects_noise_filter autoware_radar_fusion_to_detected_object autoware_radar_object_clustering autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simple_object_merger autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_mission_planner_universe autoware_obstacle_cruise_planner autoware_obstacle_stop_planner autoware_path_optimizer autoware_path_smoother autoware_planning_validator autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_run_out_module autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_run_out_module autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_component_monitor autoware_component_state_monitor autoware_default_adapi autoware_adapi_adaptors autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_processing_time_checker autoware_system_diagnostic_monitor autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor reaction_analyzer autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_mission_details_overlay_rviz_plugin autoware_overlay_rviz_plugin autoware_string_stamped_rviz_plugin autoware_perception_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_datetime_rviz_plugin tier4_localization_rviz_plugin tier4_planning_factor_rviz_plugin tier4_planning_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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Package Summary

Tags No category tags.
Version 0.44.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description
Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-04-25
Dev Status UNKNOWN
CI status No Continuous Integration
Released UNRELEASED
Tags planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

The autoware_freespace_planning_algorithms package

Additional Links

No additional links.

Maintainers

  • Kosuke Takeuchi
  • Takamasa Horibe
  • Takayuki Murooka

Authors

  • Akihito Ohsato
  • Hirokazu Ishida
planning/autoware_freespace_planning_algorithms/README.md

freespace planning algorithms

Role

This package is for development of path planning algorithms in free space.

Implemented algorithms

  • Hybrid A* and RRT* (includes RRT and informed RRT*)

Please see rrtstar.md for a note on the implementation for informed-RRT*.

NOTE: As for RRT*, one can choose whether update after feasible solution found in RRT*. If not doing so, the algorithm is the almost (but exactly because of rewiring procedure) same as vanilla RRT. If you choose update, then you have option if the sampling after feasible solution found is “informed”. If set true, then the algorithm is equivalent to informed RRT\* of Gammell et al. 2014.

Algorithm selection

There is a trade-off between algorithm speed and resulting solution quality. When we sort the algorithms by the spectrum of (high quality solution/ slow) -> (low quality solution / fast) it would be A* -> informed RRT* -> RRT. Note that in almost all case informed RRT* is better than RRT* for solution quality given the same computational time budget. So, RRT* is omitted in the comparison.

Some selection criteria would be:

  • If obstacle geometry is complex: -> avoid RRT and RRT*. The resulting path could be too messy.
  • If goal location is far from the start: -> avoid A*. Take too long time because it based on grid discretization.

Guide to implement a new algorithm

  • All planning algorithm class in this package must inherit AbstractPlanningAlgorithm class. If necessary, please overwrite the virtual functions.
  • All algorithms must use nav_msgs::OccupancyGrid-typed costmap. Thus, AbstractPlanningAlgorithm class mainly implements the collision checking using the costmap, grid-based indexing, and coordinate transformation related to costmap.
  • All algorithms must take both PlannerCommonParam-typed and algorithm-specific- type structs as inputs of the constructor. For example, AstarSearch class’s constructor takes both PlannerCommonParam and AstarParam.

Running the standalone tests and visualization

Building the package with ros-test and run tests:

colcon build --packages-select autoware_freespace_planning_algorithms
colcon test --packages-select autoware_freespace_planning_algorithms

Inside the test, simulation results are stored in /tmp/fpalgos-{algorithm_type}-case{scenario_number} as a rosbag. Loading these resulting files, by using test/debug_plot.py, one can create plots visualizing the path and obstacles as shown in the figures below. The created figures are then again saved in /tmp.

A* (single curvature case)

sample output figure

informed RRT* with 200 msec time budget

sample output figure

RRT* without update (almost same as RRT)

sample output figure

The black cells, green box, and red box, respectively, indicate obstacles, start configuration, and goal configuration. The sequence of the blue boxes indicate the solution path.

Extension to Python module (only A* supported)

There is an implementation of the extension to the python module. You can try A* search via Python by setting follows:

  • parameters,
  • costmap,
  • start pose,
  • goal pose.

Then, you can get

  • success or failure,
  • searched trajectory.

The example code is scripts/example/example.py. Note that you need to build this package and source the setup shell script in advance.

License notice

Files src/reeds_shepp.cpp and include/astar_search/reeds_shepp.h are fetched from pyReedsShepp. Note that the implementation in pyReedsShepp is also heavily based on the code in ompl. Both pyReedsShepp and ompl are distributed under 3-clause BSD license.

CHANGELOG

Changelog for package autoware_freespace_planning_algorithms

0.44.0 (2025-04-18)

0.43.0 (2025-03-21)

  • Merge remote-tracking branch 'origin/main' into chore/bump-version-0.43
  • chore: rename from [autoware.universe]{.title-ref} to [autoware_universe]{.title-ref} (#10306)
  • Contributors: Hayato Mizushima, Yutaka Kondo

0.42.0 (2025-03-03)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(autoware_utils): replace autoware_universe_utils with autoware_utils (#10191)
  • Contributors: Fumiya Watanabe, 心刚

0.41.2 (2025-02-19)

  • chore: bump version to 0.41.1 (#10088)
  • Contributors: Ryohsuke Mitsudome

0.41.1 (2025-02-10)

0.41.0 (2025-01-29)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • fix(autoware_freespace_planning_algorithms): fix bugprone-errors (#9670)
    • fix: bugprone-error

    * fix: bugprone-error ---------

  • build(autoware_freespace_planning_algorithms): increase test timeout to 2 mins (#9639)
  • Contributors: Fumiya Watanabe, M. Fatih Cırıt, kobayu858

0.40.0 (2024-12-12)

  • Merge branch 'main' into release-0.40.0
  • Revert "chore(package.xml): bump version to 0.39.0 (#9587)" This reverts commit c9f0f2688c57b0f657f5c1f28f036a970682e7f5.
  • fix: fix ticket links in CHANGELOG.rst (#9588)
  • chore(package.xml): bump version to 0.39.0 (#9587)
    • chore(package.xml): bump version to 0.39.0
    • fix: fix ticket links in CHANGELOG.rst

    * fix: remove unnecessary diff ---------Co-authored-by: Yutaka Kondo <<yutaka.kondo@youtalk.jp>>

  • fix: fix ticket links in CHANGELOG.rst (#9588)
  • fix(cpplint): include what you use - planning (#9570)
  • refactor: correct spelling (#9528)
  • fix(autoware_freespace_planner, autoware_freespace_planning_algorithms): modify freespace planner to use node clock instead of system clock (#9152)
    • Modified the autoware_freespace_planner and autoware_freespace_planning_algorithms packages to use the node clock instead of rclcpp detached clock. This allows the module to make use of sim time. Previously during simulation the parking trajectory would have system time in trajectory header messages causing downstream issues like non-clearance of trajectory buffers in motion planning based on elapsed time.
    • style(pre-commit): autofix
    • Updated the freespace planner instantiation call in the path planning modules
    • style(pre-commit): autofix
    • Updated tests for the utility functions

    * style(pre-commit): autofix ---------Co-authored-by: Steven Brills <<sbrills@oshkoshcorp.com>> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]\@users.noreply.github.com>

  • fix(autoware_freespace_planning_algorithms): fix clang-diagnostic-unused-const-variable (#9433)
  • 0.39.0
  • update changelog
  • Merge commit '6a1ddbd08bd' into release-0.39.0
  • fix: fix ticket links to point to https://github.com/autowarefoundation/autoware_universe (#9304)
  • fix(autoware_freespace_planning_algorithms): fix clang-diagnostic-ignored-optimization-argument (#9418) fix: clang-diagnostic-ignored-optimization-argument
  • fix(autoware_freespace_planning_algorithms): fix clang-diagnostic-unused-private-field (#9396)
    • fix: clang-diagnostic-unused-private-field

    * fix: build error ---------

  • fix: fix ticket links to point to https://github.com/autowarefoundation/autoware_universe (#9304)
  • chore(package.xml): bump version to 0.38.0 (#9266) (#9284)
    • unify package.xml version to 0.37.0
    • remove system_monitor/CHANGELOG.rst
    • add changelog

    * 0.38.0

  • fix(/autoware_freespace_planning_algorithms): fix cppcheck unusedFunction (#9274)
  • fix(autoware_freespace_planning_algorithms): fix bugprone-unused-raii (#9230) fix: bugprone-unused-raii
  • Contributors: Esteve Fernandez, Fumiya Watanabe, M. Fatih Cırıt, Ryohsuke Mitsudome, Ryuta Kambe, Yutaka Kondo, kobayu858, stevenbrills

0.39.0 (2024-11-25)

0.38.0 (2024-11-08)

  • unify package.xml version to 0.37.0
  • feat(freespace_planning_algorithms): implement support for multiple goal candidates in A star planner (#8092)
    • refactor freespace planning algorithms
    • fix error
    • use vector instead of map for a-star node graph
    • remove unnecessary parameters
    • precompute average turning radius
    • add threshold for minimum distance between direction changes
    • apply curvature weight and change in curvature weight
    • store total cost instead of heuristic cost
    • fix reverse weight application
    • fix parameter description in README
    • implement edt map to store distance to nearest obstacle for each grid cell
    • use obstacle edt in collision check
    • add cost for distance to obstacle
    • fix formats
    • add missing include
    • refactor functions
    • add missing include
    • implement backward search option
    • precompute number of margin cells to reduce out of range vertices check necessity
    • add reset data function
    • remove unnecessary code
    • make A-star search work with multiple goal candidates as input
    • fix is_back flag logic
    • add member function set() to AstarNode struct
    • implement adaptive expansion distance
    • remove unnecessary code
    • interpolate nodes with large expansion distance
    • minor refactor
    • fix interpolation for backward search
    • ensure expansion distance is larger than grid cell diagonal
    • compute collision free distance to goal map
    • use obstacle edt when computing collision free distance map
    • minor refactor
    • fix expansion cost function
    • set distance map before setting start node
    • refactor detect collision function
    • use flag instead of enum
    • add missing variable initialization
    • remove declared but undefined function
    • refactor makePlan() function
    • remove bool return statement for void function
    • remove unnecessary checks
    • minor fix
    • refactor computeEDTMap function
    • enable both forward and backward search options for multiple goal candidates
    • remove unnecessary code
    • set min and max expansion distance after setting costmap
    • refactor detectCollision function
    • remove unused function
    • change default parameter values
    • add missing last waypoint
    • fix computeEDTMap function
    • rename parameter
    • use linear function for obstacle distance cost
    • fix rrtstar obstacle check
    • add public access function to get distance to nearest obstacle
    • compare node index with goal index in isGoal check
    • append shifted goal pose to waypoints for more accurate arrival
    • remove redundant return statements
    • check goal pose validity before setting collision free distance map
    • declare variables as const where necessary
    • initialize vectors using assign function
    • compare front and back lengths when setting min and max dimension
    • add docstring and citation for computeEDTMap function
    • fix shifted goal pose for backward search
    • transform pose to local frame in getDistanceToObstacle funcion
    • add cost for lateral distance near goal
    • compute distance to obstacle from ego frame instead of base
    • update freespace planner parameter schema
    • update freespace planner parameter schema
    • refactor setPath function
    • fix function setPath
    • declare bool var as constant
    • remove unnecessary includes

    * minor refactor ---------Co-authored-by: Maxime CLEMENT <<78338830+maxime-clem@users.noreply.github.com>>

  • feat(freespace_planning_algorithms): implement option for backward search from goal to start (#8091)
    • refactor freespace planning algorithms
    • fix error
    • use vector instead of map for a-star node graph
    • remove unnecessary parameters
    • precompute average turning radius
    • add threshold for minimum distance between direction changes
    • apply curvature weight and change in curvature weight
    • store total cost instead of heuristic cost
    • fix reverse weight application
    • fix parameter description in README
    • implement edt map to store distance to nearest obstacle for each grid cell
    • use obstacle edt in collision check
    • add cost for distance to obstacle
    • fix formats
    • add missing include
    • refactor functions
    • add missing include
    • implement backward search option
    • precompute number of margin cells to reduce out of range vertices check necessity
    • add reset data function
    • remove unnecessary code
    • add member function set() to AstarNode struct
    • implement adaptive expansion distance
    • remove unnecessary code
    • interpolate nodes with large expansion distance
    • minor refactor
    • fix interpolation for backward search
    • ensure expansion distance is larger than grid cell diagonal
    • compute collision free distance to goal map
    • use obstacle edt when computing collision free distance map
    • minor refactor
    • fix expansion cost function
    • set distance map before setting start node
    • refactor detect collision function
    • use flag instead of enum
    • add missing variable initialization
    • remove declared but undefined function
    • refactor makePlan() function
    • remove bool return statement for void function
    • remove unnecessary checks
    • minor fix
    • refactor computeEDTMap function
    • remove unnecessary code
    • set min and max expansion distance after setting costmap
    • refactor detectCollision function
    • remove unused function
    • change default parameter values
    • add missing last waypoint
    • fix computeEDTMap function
    • rename parameter
    • use linear function for obstacle distance cost
    • fix rrtstar obstacle check
    • add public access function to get distance to nearest obstacle
    • remove redundant return statements
    • check goal pose validity before setting collision free distance map
    • declare variables as const where necessary
    • compare front and back lengths when setting min and max dimension
    • add docstring and citation for computeEDTMap function
    • transform pose to local frame in getDistanceToObstacle funcion
    • update freespace planner parameter schema
    • refactor setPath function
    • fix function setPath

    * minor refactor ---------Co-authored-by: Maxime CLEMENT <<78338830+maxime-clem@users.noreply.github.com>>

  • fix(autoware_freespace_planning_algorithms): fix variableScope (#8431) fix: variableScope Co-authored-by: kobayu858 <<129580202+kobayu858@users.noreply.github.com>>
  • chore(autoware_freespace_planning_algorithms): add missing dependency (#8494)
  • feat(freespace_planning_algorithms): use distance to nearest obstacle to improve path planning (#8089)
    • refactor freespace planning algorithms
    • fix error
    • use vector instead of map for a-star node graph
    • remove unnecessary parameters
    • precompute average turning radius
    • add threshold for minimum distance between direction changes
    • apply curvature weight and change in curvature weight
    • store total cost instead of heuristic cost
    • fix reverse weight application
    • fix parameter description in README
    • implement edt map to store distance to nearest obstacle for each grid cell
    • use obstacle edt in collision check
    • add cost for distance to obstacle
    • fix formats
    • add missing include
    • refactor functions
    • add missing include
    • precompute number of margin cells to reduce out of range vertices check necessity
    • add reset data function
    • add member function set() to AstarNode struct
    • implement adaptive expansion distance
    • remove unnecessary code
    • interpolate nodes with large expansion distance
    • minor refactor
    • ensure expansion distance is larger than grid cell diagonal
    • compute collision free distance to goal map
    • use obstacle edt when computing collision free distance map
    • minor refactor
    • fix expansion cost function
    • set distance map before setting start node
    • refactor detect collision function
    • add missing variable initialization
    • remove declared but undefined function
    • remove unnecessary checks
    • minor fix
    • refactor computeEDTMap function
    • remove unnecessary code
    • set min and max expansion distance after setting costmap
    • refactor detectCollision function
    • remove unused function
    • change default parameter values
    • fix computeEDTMap function
    • rename parameter
    • use linear function for obstacle distance cost
    • fix rrtstar obstacle check
    • remove redundant return statements
    • check goal pose validity before setting collision free distance map
    • declare variables as const where necessary
    • compare front and back lengths when setting min and max dimension
    • add docstring and citation for computeEDTMap function

    * suppress spell check ---------Co-authored-by: Maxime CLEMENT <<78338830+maxime-clem@users.noreply.github.com>>

  • fix(autoware_freespace_planning_algorithms): fix unreadVariable (#8360)
    • fix:unreadVariable

    * fix:clang format ---------

  • fix(autoware_freespace_planning_algorithms): fix functionConst (#8281) fix:functionConst
  • refactor(freespace_planning_algorithm): refactor and improve astar search (#8068)
    • refactor freespace planning algorithms
    • fix error
    • use vector instead of map for a-star node graph
    • remove unnecessary parameters
    • precompute average turning radius
    • add threshold for minimum distance between direction changes
    • apply curvature weight and change in curvature weight
    • store total cost instead of heuristic cost
    • fix reverse weight application
    • fix parameter description in README
    • fix formats
    • add missing include
    • refactor functions
    • precompute number of margin cells to reduce out of range vertices check necessity
    • add reset data function
    • add member function set() to AstarNode struct
    • remove unnecessary code
    • minor refactor
    • ensure expansion distance is larger than grid cell diagonal
    • compute collision free distance to goal map
    • minor refactor
    • fix expansion cost function
    • set distance map before setting start node
    • minor fix
    • remove unnecessary code
    • change default parameter values
    • rename parameter
    • fix rrtstar obstacle check
    • remove redundant return statements
    • check goal pose validity before setting collision free distance map

    * declare variables as const where necessary ---------

  • fix(autoware_freespace_planning_algorithms): fix shadowVariable (#7949)
    • fix:shadowVariable
    • fix:shadowVariable

    * fix:shadowVariable ---------

  • chore(freespace_planning_algorithm): modify A* script for standalone running (#7070) * modify astar for standalone running move clearNoe() from setMap to makePlan().
    • small modification

    * run pre-commit ---------Co-authored-by: Takumi Ito <<takumi.ito@tier4.jp>>

  • feat(freespace_planning_algorithms): add is_back flag into the return of A* python wrapper (#7831) add is_back flag to the return of getWaypoints Co-authored-by: Takumi Ito <<takumi.ito@tier4.jp>>
  • fix(autoware_freespace_planning_algorithms): fix syntaxError (#7812)
  • fix(autoware_freespace_planning_algorithms): fix constStatement warning (#7580)
  • fix(autoware_freespace_planning_algorithms): fix unusedScopedObject bug (#7562)
  • refactor(universe_utils/motion_utils)!: add autoware namespace (#7594)
  • feat(autoware_universe_utils)!: rename from tier4_autoware_utils (#7538) Co-authored-by: kosuke55 <<kosuke.tnp@gmail.com>>
  • refactor(freespace_planner)!: rename to include/autoware/{package_name} (#7525) refactor(freespace_planner)!: rename to include/autoware/{package_name} refactor(start_planner): make autoware include dir refactor(goal_planner): make autoware include dir sampling planner module fix sampling planner build dynamic_avoidance lc side shift autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_path_planner_common make behavior_path dir pre-commit fix pre-commit fix build autoware_freespace_planner freespace_planning_algorithms
  • refactor(vehicle_info_utils)!: prefix package and namespace with autoware (#7353)
    • chore(autoware_vehicle_info_utils): rename header
    • chore(bpp-common): vehicle info
    • chore(path_optimizer): vehicle info
    • chore(velocity_smoother): vehicle info
    • chore(bvp-common): vehicle info
    • chore(static_centerline_generator): vehicle info
    • chore(obstacle_cruise_planner): vehicle info
    • chore(obstacle_velocity_limiter): vehicle info
    • chore(mission_planner): vehicle info
    • chore(obstacle_stop_planner): vehicle info
    • chore(planning_validator): vehicle info
    • chore(surround_obstacle_checker): vehicle info
    • chore(goal_planner): vehicle info
    • chore(start_planner): vehicle info
    • chore(control_performance_analysis): vehicle info
    • chore(lane_departure_checker): vehicle info
    • chore(predicted_path_checker): vehicle info
    • chore(vehicle_cmd_gate): vehicle info
    • chore(obstacle_collision_checker): vehicle info
    • chore(operation_mode_transition_manager): vehicle info
    • chore(mpc): vehicle info
    • chore(control): vehicle info
    • chore(common): vehicle info
    • chore(perception): vehicle info
    • chore(evaluator): vehicle info
    • chore(freespace): vehicle info
    • chore(planning): vehicle info
    • chore(vehicle): vehicle info
    • chore(simulator): vehicle info
    • chore(launch): vehicle info
    • chore(system): vehicle info
    • chore(sensing): vehicle info

    * fix(autoware_joy_controller): remove unused deps ---------

  • refactor(freespace_planning_algorithms)!: add autoware prefix (#7375)
  • Contributors: Kosuke Takeuchi, M. Fatih Cırıt, Nagi70, Ryuta Kambe, Satoshi OTA, Takayuki Murooka, TakumIto, Yutaka Kondo, kobayu858, mkquda

0.26.0 (2024-04-03)

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