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HiepLM
2026-05-28 10:29:58 +07:00
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44
mir_robot/mir_navigation/config/base_local_planner_params.yaml Executable file
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base_local_planner: base_local_planner/TrajectoryPlannerROS
TrajectoryPlannerROS:
# Robot configuration
acc_lim_x: 1.5
acc_lim_y: 0
acc_lim_theta: 2.0
max_vel_x: 0.8
min_vel_x: 0.1
max_vel_theta: 1.0
min_vel_theta: -1.0
min_in_place_vel_theta: 0.2
escape_vel: -0.1
holonomic_robot: false
# Goal tolerance
yaw_goal_tolerance: 0.03
xy_goal_tolerance: 0.08
latch_xy_goal_tolerance: true
# Forward simulaton parameters
sim_time: 1.2
sim_granularity: 0.025
angular_sim_granularity: 0.04
vx_samples: 15
vtheta_samples: 20
controller_frequency: 10
# Trajectory scoring parameters
meter_scoring: true
pdist_scale: 2.2 #0.6
gdist_scale: 0.8 #0.8
occdist_scale: 0.1
heading_lookahead: 0.325
heading_scoring: true
heading_scoring_timestep: 0.8
dwa: true
publish_cost_grid: false
global_frame_id: map
# Oscillation prevention parameter
oscillation_reset_dist: 0.05
# Global plan parameters
prune_plan: true

65
mir_robot/mir_navigation/config/costmap_common_params.yaml Executable file
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robot_base_frame: $(arg prefix)base_footprint
transform_tolerance: 0.2
obstacle_range: 3.0
#mark_threshold: 1
publish_voxel_map: true
footprint_padding: 0.0
navigation_map:
map_topic: /map
virtual_walls_map:
map_topic: /virtual_walls/map
use_maximum: true
lethal_cost_threshold: 100
preferred_zones_map:
map_topic: /preferred_zones/map
lethal_cost_threshold: 100
use_maximum: true
unpreferred_zones_map:
map_topic: /unpreferred_zones/map
lethal_cost_threshold: 100
use_maximum: true
critical_zones_map:
map_topic: /critical_zones/map
lethal_cost_threshold: 100
use_maximum: true
# subscribe_to_updates: true
direction_zones_map:
map_topic: /direction_zones/map
base_frame_id: $(arg prefix)base_footprint
lethal_cost_threshold: 100
use_maximum: true
# subscribe_to_updates: true
obstacles:
observation_sources: b_scan_marking b_scan_clearing f_scan_marking f_scan_clearing
b_scan_marking:
topic: b_scan_rep117
data_type: LaserScan
clearing: false
marking: true
inf_is_valid: false
min_obstacle_height: 0.13
max_obstacle_height: 0.25
b_scan_clearing:
topic: b_scan_rep117
data_type: LaserScan
clearing: true
marking: false
inf_is_valid: false
min_obstacle_height: 0.13
max_obstacle_height: 0.25
f_scan_marking:
topic: f_scan_rep117
data_type: LaserScan
clearing: false
marking: true
inf_is_valid: false
min_obstacle_height: 0.13
max_obstacle_height: 0.25
f_scan_clearing:
topic: f_scan_rep117
data_type: LaserScan
clearing: true
marking: false
inf_is_valid: false
min_obstacle_height: 0.13
max_obstacle_height: 0.25

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mir_robot/mir_navigation/config/costmap_global_params.yaml Executable file
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global_costmap:
global_frame: map
update_frequency: 1.0
publish_frequency: 1.0
raytrace_range: 2.0
resolution: 0.05
z_resolution: 0.2
rolling_window: false
z_voxels: 10
inflation:
cost_scaling_factor: 4.0 # Exponential rate at which the obstacle cost drops off (default: 10). Must be chosen so that the cost value is > 0 at robot's circumscribed radius.
inflation_radius: 0.8 # Max. distance from an obstacle at which costs are incurred for planning paths. Must be > robot's circumscribed radius.
# plugins are loaded via costmap_global_params_plugins_[mapping|planning].yaml

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mir_robot/mir_navigation/config/costmap_global_params_plugins.yaml Executable file
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global_costmap:
frame_id: map
plugins:
- {name: navigation_map, type: "costmap_2d::StaticLayer" }
- {name: virtual_walls_map, type: "costmap_2d::StaticLayer" }
- {name: obstacles, type: "costmap_2d::VoxelLayer" }
- {name: preferred_zones_map, type: "costmap_2d::PreferredLayer" }
- {name: unpreferred_zones_map, type: "costmap_2d::UnPreferredLayer" }
- {name: direction_zones_map, type: "costmap_2d::DirectionalLayer" }
- {name: inflation, type: "costmap_2d::InflationLayer" }
- {name: critical_zones_map, type: "costmap_2d::CriticalLayer" }
# obstacles:
# track_unknown_space: true

18
mir_robot/mir_navigation/config/costmap_local_params.yaml Executable file
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local_costmap:
global_frame: $(arg prefix)odom
update_frequency: 5.0
publish_frequency: 5.0
rolling_window: true
raytrace_range: 2.0
resolution: 0.05
z_resolution: 0.15
z_voxels: 8
inflation:
cost_scaling_factor: 5.0 # Exponential rate at which the obstacle cost drops off (default: 10). Must be chosen so that the cost value is > 0 at robot's circumscribed radius.
inflation_radius: 0.8 # Max. distance from an obstacle at which costs are incurred for planning paths. Must be > robot's circumscribed radius.
width: 10.0
height: 10.0
origin_x: 0.0
origin_y: 0.0
# plugins are loaded via costmap_local_params_plugins_[mapping|planning].yaml

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mir_robot/mir_navigation/config/costmap_local_params_plugins.yaml Executable file
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local_costmap:
frame_id: odom
plugins:
- {name: virtual_walls_map, type: "costmap_2d::StaticLayer" } # các ô chi phí xung quanh "tường ảo" sẽ được tăng lên giá trị cao hơn, tạo ra một vùng an toàn xung quanh các vật cản.
- {name: obstacles, type: "costmap_2d::VoxelLayer" } # các ô chi phí xung quanh các "vật cản" sẽ được tăng lên giá trị cao hơn, tạo ra một vùng an toàn xung quanh các vật cản.
- {name: inflation, type: "costmap_2d::InflationLayer" } # các ô chi phí xung quanh các "vật cản" sẽ được tăng lên giá trị cao hơn, tạo ra một vùng an toàn xung quanh các vật cản.
# - {name: critical_zones_map, type: "costmap_2d::CriticalLayer" }

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mir_robot/mir_navigation/config/dwa_local_planner_params.yaml Executable file
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base_local_planner: dwa_local_planner/DWAPlannerROS
DWAPlannerROS:
# Robot configuration
max_vel_x: 0.8
min_vel_x: -0.2
max_vel_y: 0.0 # diff drive robot
min_vel_y: 0.0 # diff drive robot
max_trans_vel: 0.8 # choose slightly less than the base's capability
min_trans_vel: 0.1 # this is the min trans velocity when there is negligible rotational velocity
trans_stopped_vel: 0.03
# Warning!
# do not set min_trans_vel to 0.0 otherwise dwa will always think translational velocities
# are non-negligible and small in place rotational velocities will be created.
max_rot_vel: 1.0 # choose slightly less than the base's capability
min_rot_vel: 0.1 # this is the min angular velocity when there is negligible translational velocity
rot_stopped_vel: 0.1
acc_lim_x: 1.5
acc_lim_y: 0.0 # diff drive robot
acc_limit_trans: 1.5
acc_lim_theta: 2.0
# Goal tolerance
yaw_goal_tolerance: 0.03 # yaw_goal_tolerance > (sim_time * min_rot_vel) / 2 (from Navigation Tuning Guide)
xy_goal_tolerance: 0.08 # xy_goal_tolerance > (sim_time * min_vel_x) / 2
latch_xy_goal_tolerance: true
# Forward simulation
sim_time: 1.2
vx_samples: 15
vy_samples: 1 # diff drive robot, there is only one sample
vtheta_samples: 20
# Trajectory scoring
path_distance_bias: 64.0 # default: 32.0 mir: 32.0 - weighting for how much it should stick to the global path plan
goal_distance_bias: 12.0 # default: 24.0 mir: 48.0 - weighting for how much it should attempt to reach its goal
occdist_scale: 0.5 # default: 0.01 mir: 0.01 - weighting for how much the controller should avoid obstacles
forward_point_distance: 0.325 # default: 0.325 mir: 0.325 - how far along to place an additional scoring point
stop_time_buffer: 0.2 # default: 0.2 mir: 0.2 - amount of time a robot must stop before colliding for a valid traj.
scaling_speed: 0.25 # default: 0.25 mir: 0.25 - absolute velocity at which to start scaling the robot's footprint
max_scaling_factor: 0.2 # default: 0.2 mir: 0.2 - how much to scale the robot's footprint when at speed.
prune_plan: true
# Oscillation prevention
oscillation_reset_dist: 0.05 # 0.05 - how far to travel before resetting oscillation flags, in m
oscillation_reset_angle: 0.2 # 0.2 - the angle the robot must turn before resetting Oscillation flags, in rad
# Debugging
publish_traj_pc : true
publish_cost_grid_pc: true
global_frame_id: /odom # or <robot namespace>/odom

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mir_robot/mir_navigation/config/dwb_local_planner_params.yaml Executable file
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base_local_planner: nav_core_adapter::LocalPlannerAdapter
LocalPlannerAdapter:
planner_name: dwb_local_planner::DWBLocalPlanner
DWBLocalPlanner:
# Robot configuration
max_vel_x: 1.5
min_vel_x: -0.3
max_vel_y: 0.0 # diff drive robot
min_vel_y: 0.0 # diff drive robot
max_speed_xy: 2.0 # max_trans_vel: 0.8 # choose slightly less than the base's capability
min_speed_xy: 0.1 # min_trans_vel: 0.1 # this is the min trans velocity when there is negligible rotational velocity
max_vel_theta: 1.0 # max_rot_vel: 1.0 # choose slightly less than the base's capability
min_speed_theta: 0.1 # min_rot_vel: 0.1 default: 0.4 # this is the min angular velocity when there is negligible translational velocity
acc_lim_x: 0.4
acc_lim_y: 0.0 # diff drive robot
acc_lim_theta: 1.0
decel_lim_x: -1.0
decel_lim_y: -0.0
decel_lim_theta: -1.0
# Goal tolerance
yaw_goal_tolerance: 0.03 # yaw_goal_tolerance > (sim_time * min_rot_vel) / 2 (from Navigation Tuning Guide)
xy_goal_tolerance: 0.05 # xy_goal_tolerance > (sim_time * min_vel_x) / 2
# latch_xy_goal_tolerance: true
# Whether to split the path into segments or not
# Requires https://github.com/locusrobotics/robot_navigation/pull/50
split_path: true
# Forward simulation (trajectory generation)
trajectory_generator_name: dwb_plugins::StandardTrajectoryGenerator # or dwb_plugins::LimitedAccelGenerator
sim_time: 1.2
vx_samples: 12
vy_samples: 1 # diff drive robot, there is only one sample
vtheta_samples: 12
discretize_by_time: true
angular_granularity: 0.05
linear_granularity: 0.1
# sim_period
include_last_point: true
# Goal checking
goal_checker_name: dwb_plugins::SimpleGoalChecker
# stateful: true
# Critics (trajectory scoring)
# default_critic_namespaces: [dwb_critics, mir_dwb_critics]
critics: [RotateToGoal, ObstacleFootprint, PathAlign, PathDistPruned, PathProgress]
# critics: [MetratronikTechnik]
# MetratronikTechnik:
# scale: 0.01
# sq_window: 1.0
# xy_goal_tolerance: 0.02
# trans_stopped_velocity: 0.3
# slowing_factor: 1.0
# angle_threshold: 0.436332313
# Lm: 0.25
RotateToGoal:
scale: 100.0
trans_stopped_velocity: 0.25
lookahead_time: -1.0
slowing_factor: 10.0
ObstacleFootprint:
scale: 0.01 # default: 0.01 mir: 0.01 - weighting for how much the controller should avoid obstacles
max_scaling_factor: 0.5 # default: 0.2 mir: 0.2 - how much to scale the robot's footprint when at speed.
scaling_speed: 0.25 # default: 0.25 mir: 0.25 - absolute velocity at which to start scaling the robot's footprint
sum_scores: false # if true, return sum of scores of all trajectory points instead of only last one
PathAlign:
scale: 16.0
forward_point_distance: 0.325 # default: 0.325 mir: 0.325 - how far along to place an additional scoring point
PathDistPruned:
scale: 0.01 # default: 32.0 mir: 32.0 - weighting for how much it should stick to the global path plan
class: 'mir_dwb_critics::PathDistPruned'
PathProgress:
scale: 24.0 # default: 24.0 mir: 48.0 - weighting for how much it should attempt to reach its goal
heading_scale: 0.01
class: 'mir_dwb_critics::PathProgress'
xy_local_goal_tolerance: 0.5
angle_threshold: 0.523598776 # 30 degrees
# angle_threshold: 0.785398163 # 45 degrees
# Prune already passed poses from plan
prune_plan: true
prune_distance: 1.0 # Old poses farther away than prune_distance (in m) will be pruned.
# If the robot ever gets away further than this distance from the plan,
# the error "Resulting plan has 0 poses in it" will be thrown and
# replanning will be triggered.
# Debugging
publish_cost_grid_pc: true
debug_trajectory_details: false
publish_evaluation: true
publish_global_plan: true
publish_input_params: true
publish_local_plan: true
publish_trajectories: true
publish_transformed_plan: true
marker_lifetime: 0.5

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mir_robot/mir_navigation/config/eband_local_planner_params.yaml Executable file
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base_local_planner: eband_local_planner/EBandPlannerROS
EBandPlannerROS:
# Robot configuration
max_vel_lin: 0.8 # choose slightly less than the base's capability
min_vel_lin: 0.1 # this is the min trans velocity when there is negligible rotational velocity
trans_stopped_vel: 0.03
max_vel_th: 1.0 # choose slightly less than the base's capability
min_vel_th: 0.1 # this is the min angular velocity when there is negligible translational velocity
rot_stopped_vel: 0.1
min_in_place_vel_th: 0.1 # Minimum in-place angular velocity
in_place_trans_vel: 0.0 # Minimum in place linear velocity
max_acceleration: 1.5 # Maximum allowable acceleration
max_translational_acceleration: 1.5 # Maximum linear acceleration
max_rotational_acceleration: 2.0 # Maximum angular acceleration
# Goal tolerance
yaw_goal_tolerance: 0.03 # yaw_goal_tolerance > (sim_time * min_rot_vel) / 2 (from Navigation Tuning Guide)
xy_goal_tolerance: 0.08 # xy_goal_tolerance > (sim_time * min_vel_x) / 2
# Elastic Band Parameters
eband_min_relative_overlap: 0.7 # Min distance that denotes connectivity between consecutive bubbles
eband_tiny_bubble_distance: 0.01 # Bubble geometric bound regarding tiny bubble distance
eband_tiny_bubble_expansion: 0.01 # Bubble geometric bound regarding tiny bubble expansion
eband_internal_force_gain: 1.0 # Force gain of forces between consecutive bubbles that tend to stretch the elastic band
eband_external_force_gain: 2.0 # Force gain of forces that tend to move the bubbles away from obstacles
num_iterations_eband_optimization: 3 # Number of iterations for eband optimization
eband_equilibrium_approx_max_recursion_depth: 4 # Number of iterations for reaching the equilibrium between internal and external forces
eband_equilibrium_relative_overshoot: 0.75 # Maximum relative equlibrium overshoot
eband_significant_force_lower_bound: 0.15 # Minimum magnitude of force that is considered significant and used in the calculations
costmap_weight: 10.0 # Costmap weight factor used in the calculation of distance to obstacles
# Trajectory Controller Parameters
k_prop: 4.0 # Proportional gain of the PID controller
k_damp: 3.5 # Damping gain of the PID controller
Ctrl_Rate: 10.0 # Control rate
virtual_mass: 0.75 # Virtual mass
rotation_correction_threshold: 0.5 # Rotation correction threshold
differential_drive: True # Denotes whether to use the differential drive mode
bubble_velocity_multiplier: 2.0 # Multiplier of bubble radius
rotation_threshold_multiplier: 1.0 # Multiplier of rotation threshold
disallow_hysteresis: False # Determines whether to try getting closer to the goal, in case of going past the tolerance

81
mir_robot/mir_navigation/config/mir_local_planner_params.yaml Executable file
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base_local_planner: mirLocalPlanner/MIRPlannerROS
MIRPlannerROS:
# Robot configuration
max_vel_x: 0.8
min_vel_x: -0.2
min_trans_vel: 0.1 # this is the min trans velocity when there is negligible rotational velocity
# Warning!
# do not set min_trans_vel to 0.0 otherwise dwa will always think translational velocities
# are non-negligible and small in place rotational velocities will be created.
max_rot_vel: 1.0 # choose slightly less than the base's capability
min_rot_vel: 0.1 # this is the min angular velocity when there is negligible translational velocity
acc_lim_x: 1.5
acc_lim_y: 0.0 # diff drive robot
acc_lim_th: 2.0
min_inplace_rot: 0.15
max_inplace_rot: 0.6
min_in_place_rotational_vel: 0.2
escape_vel: -0.1
holonomic_robot: false
# Goal tolerance
yaw_goal_tolerance: 0.03 # yaw_goal_tolerance > (sim_time * min_rot_vel) / 2 (from Navigation Tuning Guide)
xy_goal_tolerance: 0.08 # xy_goal_tolerance > (sim_time * min_vel_x) / 2
# Forward simulaton
sim_time: 1.2
sim_granularity: 0.025
vx_samples: 15
vth_samples: 20
vtheta_samples: 20
# Trajectory scoring
path_distance_bias: 0.4 # weighting for how much it should stick to the global path plan
goal_distance_bias: 0.6 # weighting for how much it should attempt to reach its goal
occdist_scale: 0.01 # weighting for how much the controller should avoid obstacles
forward_point_distance: 0.325 # how far along to place an additional scoring point
stop_time_buffer: 0.2 # amount of time a robot must stop before colliding for a valid traj.
scaling_speed: 0.25 # absolute velocity at which to start scaling the robot's footprint
max_scaling_factor: 0.2 # how much to scale the robot's footprint when at speed.
heading_lookahead: 0.325
dwa: true
# Oscillation prevention
oscillation_reset_dist: 0.05 # how far to travel before resetting oscillation flags, in m
# Debugging
publish_visualization: false
publish_cost_grid_pc: false
global_frame_id: odom
# MiR specific parameters
tau_p: 5.0 # The proportional value in the CTE PID tracking
tau_i: 0.1 # The integral value in the CTE PID tracking
tau_d: 0.5 # The differential value in the CTE PID tracking
tau_w: 9.0 # The proportional angle value in the CTE tracking
k_rho: 1.0 # The proportional value to goal in Goal tracking
k_alfa: 8.0 # The diff angle between the robot and the goal in the Goal tracking
k_beta: -2.5 # The angle to the goal from the robot in the Goal tracking
blocked_path_dist: 3.0 # At what distance should the planner react when the path is blocked
blocked_path_dev: 60.0 # How far can we move from the planned path when it is blocked
blocked_path_action: new_plan # Which action to take, when path is blocked
occ_path_dist: 3.0 # At what distance should the planner react when the path is near obstacle
occ_path_dev: 15.0 # How far can we move from the planned path when the path is near a obstacle
occ_path_level: 120.0 # Threshold level for a obstacle
cte_look_ahead: 0.2 # The max/min distance to add for the CTE tracking
penalize_negative_x: true # Whether to penalize trajectories that have negative x velocities.
# non-dynamic parameters
dist_towards_obstacles: 1.5
dist_towards_obstacles_trolley: 1.75
goal_seek_tolerance: 2.0
goal_seek_tolerance_trolley: 0.25

46
mir_robot/mir_navigation/config/move_base_common_params.yaml Executable file
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### footprint
# footprint: [[0.488,-0.293],[0.488,0.293],[-0.412,0.293],[-0.412,-0.293]] # mir 100
footprint: [[0.405,-0.293],[0.405,0.293],[-0.412,0.293],[-0.412,-0.293]] # mir 250
# footprint: [[0.394,-0.385],[0.394,0.385],[-0.363,0.385],[-0.363,-0.385]]
### replanning
controller_frequency: 15.0 # run controller at 5.0 Hz
controller_patience: 2.0 # if the controller failed, clear obstacles and retry; after 15.0 s, abort and replan
planner_frequency: 0.0 # don't continually replan (only when controller failed)
planner_patience: 5.0 # if the first planning attempt failed, abort planning retries after 5.0 s...
max_planning_retries: 5 # ... or after 10 attempts (whichever happens first)
oscillation_timeout: 30.0 # abort controller and trigger recovery behaviors after 30.0 s
oscillation_distance: 0.3
### recovery behaviors
recovery_behavior_enabled: true
recovery_behaviors: [
{name: aggressive_reset, type: clear_costmap_recovery/ClearCostmapRecovery},
{name: conservative_reset, type: clear_costmap_recovery/ClearCostmapRecovery},
# {name: particular, type: twist_recovery/TwistRecovery},
# {name: by_pass, type: direction_zones_recovery/DirectionZonesRecovery},
]
conservative_reset:
reset_distance: 3.0 # clear obstacles farther away than 3.0 m
force_updating: true
# invert_area_to_clear: true
aggressive_reset:
reset_distance: 3.0
force_updating: true
particular:
linear_x: -0.3
linear_y: 0.0
angular_z: 0.0
duration: 1.5
# advoicedance:
# use_local_frame: false
# plan_topic: /move_base_node/SBPLLatticePlanner/plan
# planning_distance: 4.0
by_pass:
reset_distance: 8.0
force_updating: true
affected_maps: global

46
mir_robot/mir_navigation/config/pose_local_planner_params.yaml Executable file
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base_local_planner: pose_follower/PoseFollower
PoseFollower:
k_trans: 2.0
k_rot: 1.0
# within this distance to the goal, finally rotate to the goal heading (also, we've reached our goal only if we're within this dist)
tolerance_trans: 0.3
# we've reached our goal only if we're within this angular distance
tolerance_rot: 0.3
# we've reached our goal only if we're within range for this long and stopped
tolerance_timeout: 0.5
# set this to true if you're using a holonomic robot
holonomic: false
# number of samples (scaling factors of our current desired twist) to check the validity of
samples: 10
# go no faster than this
max_vel_lin: 0.3
max_vel_th: 0.5
# minimum velocities to keep from getting stuck
min_vel_lin: 0.03
min_vel_th: 0.1
# if we're rotating in place, go at least this fast to avoid getting stuck
min_in_place_vel_th: 0.1
# when we're near the end and would be trying to go no faster than this translationally, just rotate in place instead
in_place_trans_vel: 0.1
# we're "stopped" if we're going slower than these velocities
trans_stopped_velocity: 0.03
rot_stopped_velocity: 0.1
# if this is true, we don't care whether we go backwards or forwards
allow_backwards: true
# if this is true, turn in place to face the new goal instead of arcing toward it
turn_in_place_first: true
# if turn_in_place_first is true, turn in place if our heading is more than this far from facing the goal location
max_heading_diff_before_moving: 0.2

10
mir_robot/mir_navigation/config/sbpl_global_params.yaml Executable file
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base_global_planner: SBPLLatticePlanner
SBPLLatticePlanner:
environment_type: XYThetaLattice
planner_type: ARAPlanner
allocated_time: 10.0
initial_epsilon: 1.0
force_scratch_limit: 10000
forward_search: true
nominalvel_mpersecs: 0.3
timetoturn45degsinplace_secs: 1.31 # = 0.6 rad/s

105
mir_robot/mir_navigation/config/teb_local_planner_params.yaml Executable file
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# NOTE: When using the teb_local_planner, make sure to set the local costmap
# resolution high (for example 0.1 m), otherwise the optimization will take
# forever (around 10 minutes for each iteration).
base_local_planner: teb_local_planner/TebLocalPlannerROS
TebLocalPlannerROS:
# Trajectory
teb_autosize: true # Enable the automatic resizing of the trajectory during optimization (based on the temporal resolution of the trajectory, recommended)
dt_ref: 0.3 # Temporal resolution of the planned trajectory (usually it is set to the magnitude of the 1/control_rate)
dt_hysteresis: 0.1 # Hysteresis that is utilized for automatic resizing depending on the current temporal resolution (dt): usually 10% of dt_ref
global_plan_overwrite_orientation: false # Some global planners are not considering the orientation at local subgoals between start and global goal, therefore determine it automatically
allow_init_with_backwards_motion: false # If true, the underlying trajectories might be initialized with backwards motions in case the goal is behind the start within the local costmap (this is only recommended if the robot is equipped with rear sensors)
max_global_plan_lookahead_dist: 3.0 # Specify maximum length (cumulative Euclidean distances) of the subset of the global plan taken into account for optimization [if 0 or negative: disabled; the length is also bounded by the local costmap size]
force_reinit_new_goal_dist: 1.0 # Force the planner to reinitialize the trajectory if a previous goal is updated with a seperation of more than the specified value in meters (skip hot-starting)
feasibility_check_no_poses: 5 # Specify up to which pose on the predicted plan the feasibility should be checked each sampling interval
global_plan_viapoint_sep: -0.1 # Min. separation between each two consecutive via-points extracted from the global plan [if negative: disabled]
via_points_ordered: false # If true, the planner adheres to the order of via-points in the storage container
exact_arc_length: false # If true, the planner uses the exact arc length in velocity, acceleration and turning rate computations [-> increased cpu time], otherwise the euclidean approximation is used.
publish_feedback: false # Publish planner feedback containing the full trajectory and a list of active obstacles (should be enabled only for evaluation or debugging purposes)
# Robot
max_vel_x: 0.8 # Maximum translational velocity of the robot
max_vel_x_backwards: 0.2 # Maximum translational velocity of the robot for driving backwards
max_vel_y: 0.0 # Maximum strafing velocity of the robot (should be zero for non-holonomic robots!)
max_vel_theta: 1.0 # Maximum angular velocity of the robot
acc_lim_x: 1.5 # Maximum translational acceleration of the robot
acc_lim_y: 0.0 # Maximum strafing acceleration of the robot
acc_lim_theta: 2.0 # Maximum angular acceleration of the robot
min_turning_radius: 0.0 # Minimum turning radius of a carlike robot (diff-drive robot: zero)
wheelbase: 1.0 # The distance between the drive shaft and steering axle (only required for a carlike robot with 'cmd_angle_instead_rotvel' enabled); The value might be negative for back-wheeled robots!
cmd_angle_instead_rotvel: false # Substitute the rotational velocity in the commanded velocity message by the corresponding steering angle (check 'axles_distance')
is_footprint_dynamic: false # If true, update the footprint before checking trajectory feasibility
footprint_model:
type: "polygon"
vertices: [[0.506,-0.32],[0.506,0.32],[-0.454,0.32],[-0.454,-0.32]]
# Goal tolerance
xy_goal_tolerance: 0.03 # Allowed final euclidean distance to the goal position
yaw_goal_tolerance: 0.08 # Allowed final orientation error to the goal orientation
free_goal_vel: false # Allow the robot's velocity to be nonzero for planning purposes (the robot can arrive at the goal with max speed)
# Obstacles
min_obstacle_dist: 0.4 # Minimum desired separation from obstacles
inflation_dist: 0.1 # Buffer zone around obstacles with non-zero penalty costs (should be larger than min_obstacle_dist in order to take effect)
dynamic_obstacle_inflation_dist: 0.6 # Buffer zone around predicted locations of dynamic obstacles with non-zero penalty costs (should be larger than min_obstacle_dist in order to take effect)
include_dynamic_obstacles: false # Specify whether the movement of dynamic obstacles should be predicted by a constant velocity model (this also changes the homotopy class search). If false, all obstacles are considered to be static.
include_costmap_obstacles: true # Specify whether the obstacles in the costmap should be taken into account directly (this is necessary if no seperate clustering and detection is implemented)
legacy_obstacle_association: false # If true, the old association strategy is used (for each obstacle, find the nearest TEB pose), otherwise the new one (for each teb pose, find only 'relevant' obstacles).
obstacle_association_force_inclusion_factor: 1.5 # The non-legacy obstacle association technique tries to connect only relevant obstacles with the discretized trajectory during optimization, all obstacles within a specifed distance are forced to be included (as a multiple of min_obstacle_dist), e.g. choose 2.0 in order to consider obstacles within a radius of 2.0*min_obstacle_dist.
obstacle_association_cutoff_factor: 5.0 # See obstacle_association_force_inclusion_factor, but beyond a multiple of [value]*min_obstacle_dist all obstacles are ignored during optimization. obstacle_association_force_inclusion_factor is processed first.
costmap_obstacles_behind_robot_dist: 1.5 # Limit the occupied local costmap obstacles taken into account for planning behind the robot (specify distance in meters)
obstacle_poses_affected: 10 # The obstacle position is attached to the closest pose on the trajectory to reduce computational effort, but take a number of neighbors into account as well
#costmap_converter_plugin: "" #
#costmap_converter_spin_thread: true #
#costmap_converter_rate: 5 #
# Optimization
no_inner_iterations: 5 # Number of solver iterations called in each outerloop iteration
no_outer_iterations: 4 # Each outerloop iteration automatically resizes the trajectory and invokes the internal optimizer with no_inner_iterations
optimization_activate: true # Activate the optimization
optimization_verbose: false # Print verbose information
penalty_epsilon: 0.1 # Add a small safty margin to penalty functions for hard-constraint approximations
weight_max_vel_x: 2.0 # Optimization weight for satisfying the maximum allowed translational velocity
weight_max_vel_y: 2.0 # Optimization weight for satisfying the maximum allowed strafing velocity (in use only for holonomic robots)
weight_max_vel_theta: 1.0 # Optimization weight for satisfying the maximum allowed angular velocity
weight_acc_lim_x: 1.0 # Optimization weight for satisfying the maximum allowed translational acceleration
weight_acc_lim_y: 1.0 # Optimization weight for satisfying the maximum allowed strafing acceleration (in use only for holonomic robots)
weight_acc_lim_theta: 1.0 # Optimization weight for satisfying the maximum allowed angular acceleration
weight_kinematics_nh: 1000.0 # Optimization weight for satisfying the non-holonomic kinematics
weight_kinematics_forward_drive: 1.0 # Optimization weight for forcing the robot to choose only forward directions (positive transl. velocities, only diffdrive robot)
weight_kinematics_turning_radius: 1.0 # Optimization weight for enforcing a minimum turning radius (carlike robots)
weight_optimaltime: 1.0 # Optimization weight for contracting the trajectory w.r.t transition time
weight_obstacle: 50.0 # Optimization weight for satisfying a minimum seperation from obstacles
weight_inflation: 0.1 # Optimization weight for the inflation penalty (should be small)
weight_dynamic_obstacle: 50.0 # Optimization weight for satisfying a minimum seperation from dynamic obstacles
weight_dynamic_obstacle_inflation: 0.1 # Optimization weight for the inflation penalty of dynamic obstacles (should be small)
weight_viapoint: 1.0 # Optimization weight for minimizing the distance to via-points
weight_adapt_factor: 2.0 # Some special weights (currently 'weight_obstacle') are repeatedly scaled by this factor in each outer TEB iteration (weight_new: weight_old * factor); Increasing weights iteratively instead of setting a huge value a-priori leads to better numerical conditions of the underlying optimization problem.
# Homotopy Class Planner
# enable_homotopy_class_planning: true #
enable_multithreading: true # Activate multiple threading for planning multiple trajectories in parallel
# simple_exploration: false #
max_number_classes: 2 # Specify the maximum number of allowed alternative homotopy classes (limits computational effort)
selection_cost_hysteresis: 1.0 # Specify how much trajectory cost must a new candidate have w.r.t. a previously selected trajectory in order to be selected (selection if new_cost < old_cost*factor)
selection_prefer_initial_plan: 0.95 # Specify a cost reduction in the interval (0,1) for the trajectory in the equivalence class of the initial plan.)
selection_obst_cost_scale: 100.0 # Extra scaling of obstacle cost terms just for selecting the 'best' candidate (new_obst_cost: obst_cost*factor)
selection_viapoint_cost_scale: 1.0 # Extra scaling of via-point cost terms just for selecting the 'best' candidate. (new_viapt_cost: viapt_cost*factor)
selection_alternative_time_cost: false # If true, time cost is replaced by the total transition time.
roadmap_graph_no_samples: 15 # Specify the number of samples generated for creating the roadmap graph, if simple_exploration is turend off
roadmap_graph_area_width: 5.0 # Specify the width of the area in which sampled will be generated between start and goal [m] (the height equals the start-goal distance)
roadmap_graph_area_length_scale: 1.0 # The length of the rectangular region is determined by the distance between start and goal. This parameter further scales the distance such that the geometric center remains equal!)
h_signature_prescaler: 1.0 # Scale number of obstacle value in order to allow huge number of obstacles. Do not choose it extremly low, otherwise obstacles cannot be distinguished from each other (0.2<H<=1)
h_signature_threshold: 0.1 # Two h-signuteres are assumed to be equal, if both the difference of real parts and complex parts are below the specified threshold
# obstacle_keypoint_offset: 0.1 #
obstacle_heading_threshold: 0.45 # Specify the value of the normalized scalar product between obstacle heading and goal heading in order to take them (obstacles) into account for exploration)
viapoints_all_candidates: true # If true, all trajectories of different topologies are attached to the set of via-points, otherwise only the trajectory sharing the same one as the initial/global plan is attached (no effect in test_optim_node).
visualize_hc_graph: false # Visualize the graph that is created for exploring new homotopy classes
visualize_with_time_as_z_axis_scale: 0.0 # If this value is bigger than 0, the trajectory and obstacles are visualized in 3d using the time as the z-axis scaled by this value. Most useful for dynamic obstacles.
# Recovery
shrink_horizon_backup: true # Allows the planner to shrink the horizon temporary (50%) in case of automatically detected issues.
oscillation_recovery: true # Try to detect and resolve oscillations between multiple solutions in the same equivalence class (robot frequently switches between left/right/forward/backwards).
odom_topic: odom
map_frame: odom