ellensohn/cps_rmp220_support
1
0
Fork 0
mirror of https://github.com/bjoernellens1/cps_rmp220_support.git synced 2024-11-23 15:45:08 +00:00
Code Issues Packages Projects Releases Wiki Activity

update

Browse Source
This commit is contained in:
Björn Ellensohn 2023-09-08 10:10:20 +02:00
parent e8d5eba465
commit a25dea1372
1 changed files with 1 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
config/nav2_params.yaml
View File

@ -545,7 +545,7 @@ planner_server:
analytic_expansion_ratio: 3.5 # The ratio to attempt analytic expansions during search for final approach. 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 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: 0.15 # was 0.40 # minimum turning radius in m of path / vehicle minimum_turning_radius: 0.15 # was 0.40 # minimum turning radius in m of path / vehicle
reverse_penalty: 1.0 # was 2.0 # Penalty to apply if motion is reversing, must be => 1 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 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 non_straight_penalty: 1.2 # Penalty to apply if motion is non-straight, must be => 1
cost_penalty: 2.0 # 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. cost_penalty: 2.0 # 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.