Tune MKMini Reeds-Shepp navigation

This commit is contained in:
2026-08-19 09:53:09 +09:00
parent d23e15c5dc
commit b9da8b0c30
2 changed files with 8 additions and 5 deletions
@@ -5,7 +5,10 @@
<root main_tree_to_execute="MainTree"> <root main_tree_to_execute="MainTree">
<BehaviorTree ID="MainTree"> <BehaviorTree ID="MainTree">
<PipelineSequence name="NavigateToPose"> <PipelineSequence name="NavigateToPose">
<RateController hz="1.0"> <!-- Reeds-Shepp direction choices can flip when a car-like path is
recomputed every second. The static Gazebo world only needs a
low-rate refresh while the controller follows the current arc. -->
<RateController hz="0.1">
<ComputePathToPose goal="{goal}" path="{path}" planner_id="GridBased"/> <ComputePathToPose goal="{goal}" path="{path}" planner_id="GridBased"/>
</RateController> </RateController>
<FollowPath path="{path}" controller_id="FollowPath"/> <FollowPath path="{path}" controller_id="FollowPath"/>
@@ -107,16 +107,16 @@ planner_server:
max_iterations: 3000000 max_iterations: 3000000
max_on_approach_iterations: 5000 max_on_approach_iterations: 5000
max_planning_time: 10.0 max_planning_time: 10.0
# Normal navigation should remain forward-only. Reeds-Shepp creates # Test car-like paths that can reverse to leave constrained spaces.
# forward/reverse cusps that Regulated Pure Pursuit can oscillate on. motion_model_for_search: "REEDS_SHEPP"
motion_model_for_search: "DUBIN"
angle_quantization_bins: 144 angle_quantization_bins: 144
analytic_expansion_ratio: 3.5 analytic_expansion_ratio: 3.5
analytic_expansion_max_length: 5.0 analytic_expansion_max_length: 5.0
# tricycle_drive uses a 0.72 m wheelbase with a 0.5 rad steering limit. # tricycle_drive uses a 0.72 m wheelbase with a 0.5 rad steering limit.
# 0.72 / tan(0.5) is 1.32 m; keep a small planning margin. # 0.72 / tan(0.5) is 1.32 m; keep a small planning margin.
minimum_turning_radius: 1.35 minimum_turning_radius: 1.35
change_penalty: 0.0 # Prefer a continuous arc over avoidable forward/reverse oscillation.
change_penalty: 1.0
non_straight_penalty: 1.5 non_straight_penalty: 1.5
cost_penalty: 5.0 cost_penalty: 5.0
retrospective_penalty: 0.1 retrospective_penalty: 0.1