navigation stack with teb_local_planner planning path through wall
Hello! I'm currently trying to use teb_local_planner to get my robot to navigate through the willow garage simulation. However, I have the issue that in specific situations the local path planning attemtps to drive through the wall. Ofcourse, this doesn't work and it figures that out quite quickly. After a while though, it attempts to go through the wall again. This sometimes loops for over 2 minutes. I have a video where you can see it happen two times.
I'm using mostly the default settings from navigation stack as you can see in the code-quotes below. Can anyone help me figure out why the local costmap is trying to drive through walls sometimes (and gets stuck in a loop of switching in between trying to drive through wall and the actual route it should take)
launch file:
<launch>
<!-- Run the map server -->
<node name="gmapping" pkg="gmapping" type="slam_gmapping"/>
<node pkg="move_base" type="move_base" respawn="false" name="move_base" output="screen">
<rosparam file="$(find my_robot_name_2dnav)/costmap_common_params.yaml" command="load" ns="global_costmap" />
<rosparam file="$(find my_robot_name_2dnav)/costmap_common_params.yaml" command="load" ns="local_costmap"/>
<rosparam file="$(find my_robot_name_2dnav)/local_costmap_params.yaml" command="load" />
<rosparam file="$(find my_robot_name_2dnav)/global_costmap_params.yaml" command="load" />
<rosparam file="$(find my_robot_name_2dnav)/base_local_planner_params.yaml" command="load" />
<param name="base_local_planner" value="teb_local_planner/TebLocalPlannerROS" />
<param name="controller_frequency" value="4.0" />
</node>
</launch>
costmap_common_params.yaml
obstacle_range: 2.5
raytrace_range: 3.0
footprint: [[-0.20, -0.20], [-0.20, 0.20], [0.20, 0.20], [0.20, -0.20]]
#robot_radius: ir_of_robot
inflation_radius: 1
observation_sources: scan
scan: {data_type: LaserScan, expected_update_rate: 0.4,
observation_persistence: 0.0, marking: true, clearing: true, max_obstacle_height: 0.4, min_obstacle_height: 0.08}
cost_scaling_factor: 1
base_local_planner_params.yaml
TebLocalPlannerROS:
odom_topic: odom
# Trajectory
teb_autosize: True
dt_ref: 0.3
dt_hysteresis: 0.1
global_plan_overwrite_orientation: True
max_global_plan_lookahead_dist: 3.0
feasibility_check_no_poses: 5
# Robot
max_vel_x: 0.4
max_vel_x_backwards: 0.05 #0.2 by default
max_vel_theta: 0.3
acc_lim_x: 0.5
acc_lim_theta: 0.5
min_turning_radius: 0.0 # diff-drive robot (can turn on place!)
footprint_model:
type: "point"
# GoalTolerance
xy_goal_tolerance: 0.2
yaw_goal_tolerance: 0.1
free_goal_vel: False
# Obstacles
min_obstacle_dist: 0.25 # This value must also include our robot radius, since footprint_model is set to "point".
include_costmap_obstacles: True
costmap_obstacles_behind_robot_dist: 1.0
obstacle_poses_affected: 30
costmap_converter_plugin: ""
costmap_converter_spin_thread: True
costmap_converter_rate: 5
# Optimization
no_inner_iterations: 5
no_outer_iterations: 4
optimization_activate: True
optimization_verbose: False
penalty_epsilon: 0.1
weight_max_vel_x: 2
weight_max_vel_theta: 1
weight_acc_lim_x: 1
weight_acc_lim_theta: 1
weight_kinematics_nh: 1000
weight_kinematics_forward_drive: 1
weight_kinematics_turning_radius: 1
weight_optimaltime: 1
weight_obstacle: 50
weight_dynamic_obstacle: 10 # not in use yet
# Homotopy Class Planner
enable_homotopy_class_planning: True
enable_multithreading: True
simple_exploration: False
max_number_classes: 4
selection_cost_hysteresis: 1.0
selection_obst_cost_scale: 1.0
selection_alternative_time_cost: False
roadmap_graph_no_samples: 15
roadmap_graph_area_width: 5
h_signature_prescaler: 0.5
h_signature_threshold: 0.1
obstacle_keypoint_offset: 0.1
global_costmap_params.yaml
global_costmap:
global_frame: /map
robot_base_frame: base_link
update_frequency: 5.0
static_map: true
local_costmap_params.yaml
local_costmap:
global_frame: odom
robot_base_frame: base_link
update_frequency: 5.0
publish_frequency: 2.0
static_map: false
rolling_window: true
width: 6.0
height: 6.0
resolution: 0.05
