update

config/nav2_params.yaml

@@ -576,58 +576,58 @@ map_saver:
     occupied_thresh_default: 0.65
     map_subscribe_transient_local: True
 
-# planner_server:
-#   ros__parameters:
-#     expected_planner_frequency: 20.0
-#     use_sim_time: False
-#     planner_plugins: ["GridBased"]
-#     GridBased:
-#       plugin: "nav2_navfn_planner/NavfnPlanner"
-#       #plugin: "nav2_smac_planner/SmacPlanner2D"
-#       tolerance: 0.5
-#       #use_astar: false
-#       allow_unknown: true
-
-# trying smac hybrid planner
 planner_server:
   ros__parameters:
+    expected_planner_frequency: 20.0
+    use_sim_time: False
     planner_plugins: ["GridBased"]
-    use_sim_time: True
-
     GridBased:
-      plugin: "nav2_smac_planner/SmacPlannerHybrid"
+      plugin: "nav2_navfn_planner/NavfnPlanner"
-      downsample_costmap: false           # whether or not to downsample the map
+      #plugin: "nav2_smac_planner/SmacPlanner2D"
-      downsampling_factor: 1              # multiplier for the resolution of the costmap layer (e.g. 2 on a 5cm costmap would be 10cm)
+      tolerance: 0.5
-      tolerance: 0.25                     # dist-to-goal heuristic cost (distance) for valid tolerance endpoints if exact goal cannot be found.
+      #use_astar: false
-      allow_unknown: true                 # allow traveling in unknown space
+      allow_unknown: true
-      max_iterations: 1000000             # maximum total iterations to search for before failing (in case unreachable), set to -1 to disable
-      max_on_approach_iterations: 1000    # Maximum number of iterations after within tolerances to continue to try to find exact solution
-      max_planning_time: 5.0              # max time in s for planner to plan, smooth
-      motion_model_for_search: "DUBIN" #was DUBIN   # Hybrid-A* Dubin, Redds-Shepp
-      angle_quantization_bins: 72         # Number of angle bins for search
-      analytic_expansion_ratio: 3.5       # The ratio to attempt analytic expansions during search for final approach.
-      analytic_expansion_max_length: 3.0  # For Hybrid/Lattice nodes: The maximum length of the analytic expansion to be considered valid to prevent unsafe shortcutting
-      minimum_turning_radius: 0.10 # was 0.40        # minimum turning radius in m of path / vehicle
-      reverse_penalty: 1.3 # was 2.0               # Penalty to apply if motion is reversing, must be => 1
-      change_penalty: 0.5 # was 0.0                # Penalty to apply if motion is changing directions (L to R), must be >= 0
-      non_straight_penalty: 1.2           # Penalty to apply if motion is non-straight, must be => 1
-      cost_penalty: 3.0 # was 2 before                   # Penalty to apply to higher cost areas when adding into the obstacle map dynamic programming distance expansion heuristic. This drives the robot more towards the center of passages. A value between 1.3 - 3.5 is reasonable.
-      retrospective_penalty: 0.015
-      lookup_table_size: 20.0             # Size of the dubin/reeds-sheep distance window to cache, in meters.
-      cache_obstacle_heuristic: true #was fasle     # Cache the obstacle map dynamic programming distance expansion heuristic between subsiquent replannings of the same goal location. Dramatically speeds up replanning performance (40x) if costmap is largely static.
-      debug_visualizations: false         # For Hybrid nodes: Whether to publish expansions on the /expansions topic as an array of poses (the orientation has no meaning) and the path's footprints on the /planned_footprints topic. WARNING: heavy to compute and to display, for debug only as it degrades the performance.
-      use_quadratic_cost_penalty: False
-      downsample_obstacle_heuristic: True
-      allow_primitive_interpolation: False
-      smooth_path: True                   # If true, does a simple and quick smoothing post-processing to the path
 
-      smoother:
+# trying smac hybrid planner
-        max_iterations: 1000
+# planner_server:
-        w_smooth: 0.3
+#   ros__parameters:
-        w_data: 0.2
+#     planner_plugins: ["GridBased"]
-        tolerance: 1.0e-10
+#     use_sim_time: True
-        do_refinement: true
+
-        refinement_num: 2
+#     GridBased:
+#       plugin: "nav2_smac_planner/SmacPlannerHybrid"
+#       downsample_costmap: false           # whether or not to downsample the map
+#       downsampling_factor: 1              # multiplier for the resolution of the costmap layer (e.g. 2 on a 5cm costmap would be 10cm)
+#       tolerance: 0.25                     # dist-to-goal heuristic cost (distance) for valid tolerance endpoints if exact goal cannot be found.
+#       allow_unknown: true                 # allow traveling in unknown space
+#       max_iterations: 1000000             # maximum total iterations to search for before failing (in case unreachable), set to -1 to disable
+#       max_on_approach_iterations: 1000    # Maximum number of iterations after within tolerances to continue to try to find exact solution
+#       max_planning_time: 5.0              # max time in s for planner to plan, smooth
+#       motion_model_for_search: "DUBIN" #was DUBIN   # Hybrid-A* Dubin, Redds-Shepp
+#       angle_quantization_bins: 72         # Number of angle bins for search
+#       analytic_expansion_ratio: 3.5       # The ratio to attempt analytic expansions during search for final approach.
+#       analytic_expansion_max_length: 3.0  # For Hybrid/Lattice nodes: The maximum length of the analytic expansion to be considered valid to prevent unsafe shortcutting
+#       minimum_turning_radius: 0.10 # was 0.40        # minimum turning radius in m of path / vehicle
+#       reverse_penalty: 1.3 # was 2.0               # Penalty to apply if motion is reversing, must be => 1
+#       change_penalty: 0.5 # was 0.0                # Penalty to apply if motion is changing directions (L to R), must be >= 0
+#       non_straight_penalty: 1.2           # Penalty to apply if motion is non-straight, must be => 1
+#       cost_penalty: 3.0 # was 2 before                   # Penalty to apply to higher cost areas when adding into the obstacle map dynamic programming distance expansion heuristic. This drives the robot more towards the center of passages. A value between 1.3 - 3.5 is reasonable.
+#       retrospective_penalty: 0.015
+#       lookup_table_size: 20.0             # Size of the dubin/reeds-sheep distance window to cache, in meters.
+#       cache_obstacle_heuristic: true #was fasle     # Cache the obstacle map dynamic programming distance expansion heuristic between subsiquent replannings of the same goal location. Dramatically speeds up replanning performance (40x) if costmap is largely static.
+#       debug_visualizations: false         # For Hybrid nodes: Whether to publish expansions on the /expansions topic as an array of poses (the orientation has no meaning) and the path's footprints on the /planned_footprints topic. WARNING: heavy to compute and to display, for debug only as it degrades the performance.
+#       use_quadratic_cost_penalty: False
+#       downsample_obstacle_heuristic: True
+#       allow_primitive_interpolation: False
+#       smooth_path: True                   # If true, does a simple and quick smoothing post-processing to the path
+
+#       smoother:
+#         max_iterations: 1000
+#         w_smooth: 0.3
+#         w_data: 0.2
+#         tolerance: 1.0e-10
+#         do_refinement: true
+#         refinement_num: 2
 
 smoother_server:
   ros__parameters: