Nav2 - global_planner does not avoid obstacles
Hi,
I am tunning nav2 parameters for a rectangular robot, when I send a goal that requires obstacle avoidance the planner does not avoid the obstacle, here is my param file and screenshot. Thanks for help.
amcl:
ros__parameters:
use_sim_time: True
alpha1: 0.2
alpha2: 0.2
alpha3: 0.2
alpha4: 0.2
alpha5: 0.2
base_frame_id: "base_footprint"
beam_skip_distance: 0.5
beam_skip_error_threshold: 0.9
beam_skip_threshold: 0.3
do_beamskip: false
global_frame_id: "map"
lambda_short: 0.1
laser_likelihood_max_dist: 2.0
laser_max_range: 100.0
laser_min_range: -1.0
laser_model_type: "likelihood_field"
max_beams: 60
max_particles: 2000
min_particles: 500
odom_frame_id: "odom"
pf_err: 0.05
pf_z: 0.99
recovery_alpha_fast: 0.0
recovery_alpha_slow: 0.0
resample_interval: 1
robot_model_type: "differential"
save_pose_rate: 0.5
sigma_hit: 0.2
tf_broadcast: true
transform_tolerance: 1.0
update_min_a: 0.01
update_min_d: 0.2
z_hit: 0.5
z_max: 0.05
z_rand: 0.5
z_short: 0.05
scan_topic: scan_front
map_topic: map
amcl_map_client:
ros__parameters:
use_sim_time: True
amcl_rclcpp_node:
ros__parameters:
use_sim_time: True
bt_navigator:
ros__parameters:
use_sim_time: True
global_frame: "map"
robot_base_frame: "base_link"
odom_topic: /odom
enable_groot_monitoring: True
groot_zmq_publisher_port: 1666
groot_zmq_server_port: 1667
default_bt_xml_filename: "navigate_w_replanning_and_recovery.xml"
plugin_lib_names:
- nav2_compute_path_to_pose_action_bt_node
- nav2_follow_path_action_bt_node
- nav2_back_up_action_bt_node
- nav2_spin_action_bt_node
- nav2_wait_action_bt_node
- nav2_clear_costmap_service_bt_node
- nav2_is_stuck_condition_bt_node
- nav2_goal_reached_condition_bt_node
- nav2_goal_updated_condition_bt_node
- nav2_initial_pose_received_condition_bt_node
- nav2_reinitialize_global_localization_service_bt_node
- nav2_rate_controller_bt_node
- nav2_distance_controller_bt_node
- nav2_speed_controller_bt_node
- nav2_truncate_path_action_bt_node
- nav2_goal_updater_node_bt_node
- nav2_recovery_node_bt_node
- nav2_pipeline_sequence_bt_node
- nav2_round_robin_node_bt_node
- nav2_transform_available_condition_bt_node
- nav2_time_expired_condition_bt_node
- nav2_distance_traveled_condition_bt_node
bt_navigator_rclcpp_node:
ros__parameters:
use_sim_time: True
controller_server:
ros__parameters:
use_sim_time: True
controller_frequency: 5.0
min_x_velocity_threshold: 0.001
min_y_velocity_threshold: 0.5
min_theta_velocity_threshold: 0.001
progress_checker_plugin: "progress_checker"
goal_checker_plugin: "goal_checker"
controller_plugins: ["FollowPath"]
# Progress checker parameters
progress_checker:
plugin: "nav2_controller::SimpleProgressChecker"
required_movement_radius: 0.5
movement_time_allowance: 10.0
# Goal checker parameters
goal_checker:
plugin: "nav2_controller::SimpleGoalChecker"
xy_goal_tolerance: 0.25
yaw_goal_tolerance: 0.25
stateful: True
# DWB parameters
FollowPath:
plugin: "dwb_core::DWBLocalPlanner"
debug_trajectory_details: True
min_vel_x: 0.0
min_vel_y: 0.0
max_vel_x: 1.5
max_vel_y: 0.0
max_vel_theta: 1.0
min_speed_xy: 0.0
max_speed_xy: 1.0
min_speed_theta: 0.0
acc_lim_x: 2.5
acc_lim_y: 0.0
acc_lim_theta: 3.2
decel_lim_x: -2.5
decel_lim_y: 0.0
decel_lim_theta: -3.2
vx_samples: 20
vy_samples: 5
vtheta_samples: 20
sim_time: 1.7
linear_granularity: 0.05
angular_granularity: 0.025
transform_tolerance: 0.2
xy_goal_tolerance: 0.25
trans_stopped_velocity: 0.25
short_circuit_trajectory_evaluation: True
stateful: True
critics: ["RotateToGoal", "Oscillation", "ObstacleFootprint", "GoalAlign", "PathAlign", "PathDist", "GoalDist"] # ObstacleFootprint pour notre robot (non circulaire)
ObstacleFootprint.scale: 0.02 # meme chose
PathAlign.scale: 32.0
PathAlign.forward_point_distance: 0.1
GoalAlign.scale: 24.0
GoalAlign.forward_point_distance: 0.1
PathDist.scale: 32.0
GoalDist.scale: 24.0
RotateToGoal.scale: 32.0
RotateToGoal.slowing_factor: 5.0
RotateToGoal.lookahead_time: -1.0
controller_server_rclcpp_node:
ros__parameters:
use_sim_time: True
local_costmap:
local_costmap:
ros__parameters:
update_frequency: 5.0
publish_frequency: 2.0
global_frame: "map"
robot_base_frame: "base_link"
use_sim_time: True
rolling_window: true
width: 5
height: 5
resolution: 0.05
map_topic: "map"
origin_x: -24.9
origin_y: -24.9
footprint_padding: 0.01
footprint: "[[-0.7874, -0.381], [-0.7874, 0.381], [0.8636, 0.381], [0.8636, -0.381]]"
plugins: ["obstacle_layer", "inflation_layer"]
inflation_layer:
plugin: "nav2_costmap_2d::InflationLayer"
cost_scaling_factor: 3.0
inflation_radius: 0.55
obstacle_layer:
plugin: "nav2_costmap_2d::ObstacleLayer"
enabled: True
observation_sources: scan
scan:
topic: /scan_front
max_obstacle_height: 2.0
clearing: True
marking: True
data_type: "LaserScan"
static_layer:
map_subscribe_transient_local: True
always_send_full_costmap: True
local_costmap_client:
ros__parameters:
use_sim_time: True
local_costmap_rclcpp_node:
ros__parameters:
use_sim_time: True
global_costmap:
global_costmap:
ros__parameters:
update_frequency: 1.0
publish_frequency: 1.0
global_frame: map
robot_base_frame: base_link
use_sim_time: True
footprint_padding: 0.01
footprint ...
I've experienced the same behavior. There is a major bug in Foxy version at least. Robot plans straight through obstacles because the costmap at that point in time is completely empty for some reason. Modifying source code to check if that's the case solves the problem, but i would suggest switching to more recent version of nav2
@avzmpy thanks, but that's weird because turtlebot3 simulation is working fine !! is there a ticket for that bug on work ?