global_planner_params.yaml参考文件

# Global Planner Parameters

# maximum distance to the goal point
goal_distance_tolerance: 0.1

# maximum allowed numerical error for goal position
xy_goal_tolerance: 0.2

# maximum allowed numerical error for goal orientation
yaw_goal_tolerance: 0.3

# weight for the heuristic function used in the A* algorithm
# higher values prefer straighter paths, lower values prefer paths with less turning
heuristic_weight: 3.0

# minimum distance to travel before attempting to replan
min_replan_distance: 1.0

# minimum amount of time to wait before attempting to replan
min_replan_time: 1.0

# tolerance on the robot's heading (in radians) when planning
# during rotation commands this is an additional error that gets added to
# yaw_goal_tolerance
heading_lookahead: 0.325

# minimum lookahead to do during path planning. A shorter lookahead is more
# cautious (especially in tight spaces) but may be more effective at avoiding
# collisions with complex obstacles
min_lookahead_distance: 0.4

# maximum lookahead to do during path planning
max_lookahead_distance: 2.0

# if true, the global planner will only plan one step at a time
# rather than to the final goal state
intermediate_planning: false

# what topic the planner should use for status feedback
planner_frequency: 0.5
planner_topic: "planner_status"

# how close the robot must be to the global plan before updating it with
# a new one
plan_update_distance: 0.5

# how often the planner should be allowed to make new plans. A value of 0
# means plans will be made as often as possible
planner_patience: 5.0

# penalty for robot rotation during path planning. A higher penalty will
# cause the planner to prefer straighter paths with less turns
rotation_penalty: 0.8

# maximum absolute rotation speed allowed while navigating along the global
# plan
max_rotation_speed: 1.0

# maximum speed to travel along the global plan
max_velocity: 0.6

# If true, the global planner will try to avoid obstacles with a combination
# of steering and braking. Otherwise, it will only steer around obstacles
braking_enabled: true

# how many times to retry a goal update if the previous attempt resulted in a
# collision or other error.
# If set to -1, it will retry indefinitely
goal_update_retries: 3

# Whether or not to use the extrinsic rotation control method in the planner
use_extrinsic_rotation: true

# Enabling this parameter causes the global planner to use
# differential constraints for smoother trajectories
use_differential_constraints: true

# Enabling this parameter causes the planner to assume the
# robot is driving on the right-hand side of the street
drive_on_right: true

# Timeout for the planning process (in seconds). If planning takes longer
# than this, the planner will abort and return a failure status
planning_timeout: 5.0

# If set, this parameter limits the maximum planning distance the
# planner will use. Set to -1 for no limit.
max_planning_distance: -1

# Enabling this parameter causes the planner to ignore the robot's ground
# clearance when planning.
ignore_ground_clearance: false

# Whether the planner should try to avoid going backwards
avoid_going_backwards: false

# The maximum distance (in meters) that the planner will consider changing
# the orientation of the robot to better follow the path. Set to -1 to
# disable this behavior.
max_orientation_change: 0.9

# The minimum distance (in meters) that the planner will consider
# detecting a change in orientation of the robot to better follow the path.
# Set to -1 to disable this behavior.
min_orientation_change: 0.5

# Whether the planner should attempt to use the current local plan when planning.
# If set to true, the planner will attempt to connect the current local plan
# to the new plan. If set to false, the planner will always start from the robot's
# current pose.
use_local_plan: true

# Whether the planner should attempt to use the current local costmap when planning.
# If set to true, the planner will use the local costmap to build an estimate
# of the robot's surroundings. If set to false, the planner will only use the
# global costmap.
use_local_costmap: true

# Whether the planner should use the old behavior of setting waypoints to
# the right of the global plan. This behavior causes the robot to execute
# the plan with a rightward shift. However, it can be problematic if the plan
# encounters obstacles on the left side.
use_typical_rightward_shift: false

# Whether the planner should use a zero velocity as a way to avoid oscillations.
# If set to true, the planner will stop the robot and wait for the current goal
# to either become unreachable or within the goal tolerance.
stop_when_goal_rejected: false

# The time (in seconds) that the planner will stop and wait (in case of oscillations)
# before trying to replan.
stop_and_wait_time: 2.0

# Distance (in meters) to be left before the end of the path. This can be useful
# when the robot should stop at a certain distance from the goal pose.
path_distance_offset: 0

# Maximum allowed speed deviation from the global plan (in m/s).
max_allowed_speed_deviation: 1.0

# Maximum allowed angular deviation from the global plan (in rad).
max_allowed_angular_deviation: 1.57

# Whether or not to use a linear navigation function to bias global plan costs toward closer parts of the map.
use_linear_navigation_function: false

# Whether or not to use a terrain independent cost scale to bias global plan costs toward flatter regions.
use_terrain_independent_cost_scale: true

# The maximum number of obstacles to check against during planning.
max_obstacle_check_count: 500

# If true, the planner will skip planning during the first update cycle after initialization.
skip_initial_planning: false

# Scaling factor for the distances used in the Adaptive Sampling Path algorithm
as_scaler: 1.0

# The maximum length of the Adaptive Sampling Path segments
as_max_segment_length: 1.0

# The turning radius for the robot used in the prediction step of the Adaptive Sampling Path algorithm
as_robot_radius: 0.3

# The number of areas forward used for heading smoothing in the Adaptive Sampling Path algorithm.
# Set to 0 if heading smoothing is not desired.
as_heading_smoothing_areas: 0

# The maximum distance the Adaptive Sampling Path algorithm will plan for.
# Set to -1 for no limit.
as_max_global_plan_distance: -1

# How many layers of costmaps to plan in. A higher value will allow the global
# planner to take into account more layers of static and dynamic obstacles.
# 0 means only use the base global costmap.
planning_layers: 0