path_planner_configuration

#AMCL IS NOT NEEDED FOR OUTDOOR GPS BASED NAVIGATION!

# 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: 10000 #2000
#     min_particles: 2000 #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:  "omnidirectional" #"differential" #
#     save_pose_rate: 0.5
#     sigma_hit: 0.2
#     tf_broadcast: true
#     transform_tolerance: 1.0
#     update_min_a: 0.2
#     update_min_d: 0.25
#     z_hit: 0.5
#     z_max: 0.05
#     z_rand: 0.5
#     z_short: 0.05
#     scan_topic: fused_scan #left_scan #kinect_sensor/scan

# 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
    bt_loop_duration: 10
    default_server_timeout: 20
    enable_groot_monitoring: True
    groot_zmq_publisher_port: 1666
    groot_zmq_server_port: 1667
    # 'default_nav_through_poses_bt_xml' and 'default_nav_to_pose_bt_xml' are use defaults:
    # nav2_bt_navigator/navigate_to_pose_w_replanning_and_recovery.xml
    # nav2_bt_navigator/navigate_through_poses_w_replanning_and_recovery.xml
    # They can be set here or via a RewrittenYaml remap from a parent launch file to Nav2.
    plugin_lib_names:
    - nav2_compute_path_to_pose_action_bt_node
    - nav2_compute_path_through_poses_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
    - nav2_single_trigger_bt_node
    - nav2_is_battery_low_condition_bt_node
    - nav2_navigate_through_poses_action_bt_node
    - nav2_navigate_to_pose_action_bt_node
    - nav2_remove_passed_goals_action_bt_node
    - nav2_planner_selector_bt_node
    - nav2_controller_selector_bt_node
    - nav2_goal_checker_selector_bt_node

bt_navigator_rclcpp_node:
  ros__parameters:
    use_sim_time: True

controller_server:
  ros__parameters:
    use_sim_time: True
    controller_frequency: 20.0
    min_x_velocity_threshold: 0.01 #0.001
    min_y_velocity_threshold: 0.5
    min_theta_velocity_threshold: 0.01 #0.001
    failure_tolerance: 1.0 #0.3
    progress_checker_plugin: "progress_checker"
    goal_checker_plugins: ["general_goal_checker"] # "precise_goal_checker"
    controller_plugins: ["FollowPath"]

    # Progress checker parameters
    progress_checker:
      plugin: "nav2_controller::SimpleProgressChecker"
      required_movement_radius: 0.5 #1.0 #0.5
      movement_time_allowance: 10.0
    # Goal checker parameters
    # precise_goal_checker:
    #  plugin: "nav2_controller::SimpleGoalChecker"
    #  xy_goal_tolerance: 1.0
    #  yaw_goal_tolerance: 1.0
    #  stateful: True
    general_goal_checker:
      stateful: True
      plugin: "nav2_controller::SimpleGoalChecker"
      xy_goal_tolerance: 3.0 #0.25
      yaw_goal_tolerance: 25.0 #0.25
    # DWB parameters
    FollowPath:
      plugin: "dwb_core::DWBLocalPlanner"
      debug_trajectory_details: True
      min_vel_x: 0.0
      min_vel_y: 0.0
      max_vel_x: 15.0
      max_vel_y: 0.0
      max_vel_theta: 10.0
      min_speed_xy: 0.0
      max_speed_xy: 26.0
      min_speed_theta: 0.0
      # Add high threshold velocity for turtlebot 3 issue.
      # https://github.com/ROBOTIS-GIT/turtlebot3_simulations/issues/75
      acc_lim_x: 25.0
      acc_lim_y: 0.0
      acc_lim_theta: 25.0
      decel_lim_x: -25.0
      decel_lim_y: 0.0
      decel_lim_theta: -25.0
      vx_samples: 20
      vy_samples: 5
      vtheta_samples: 20
      sim_time: 1.7
      linear_granularity: 0.05 #0.05 # Distance between consecutive points in the path. Lower values increase resolution but also computational cost.
      angular_granularity: 0.25 #0.025 # Minimum change in orientation between path points. Smaller values lead to smoother turns but higher computational expense
      transform_tolerance: 0.2
      xy_goal_tolerance: 2.0 #0.25
      trans_stopped_velocity: 0.25
      short_circuit_trajectory_evaluation: True
      stateful: True
      critics: ["RotateToGoal", "Oscillation", "BaseObstacle", "GoalAlign", "PathAlign", "PathDist", "GoalDist"]
      BaseObstacle.scale: 0.02
      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:
      #Added below to enable slam
      unknown_cost_value: 255
      lethal_cost_threshold: 100
      update_frequency: 5.0
      publish_frequency: 2.0
      global_frame: odom
      robot_base_frame: base_link
      use_sim_time: True
      rolling_window: true
      width: 50
      height: 50
      resolution: 0.2
      #robot_radius: 0.22
      footprint:  "[[-4.8025, -1.739], [4.8025, -1.739], [4.8025, 1.739], [-4.8025, 1.739]]"
      plugins: ["voxel_layer", "inflation_layer"]
      inflation_layer:
        plugin: "nav2_costmap_2d::InflationLayer"
        cost_scaling_factor: 1.0 #3.0
        inflation_radius: 0.5 #2.0 #0.55
      voxel_layer:
        plugin: "nav2_costmap_2d::VoxelLayer"
        enabled: True
        publish_voxel_map: True
        origin_z: 2.0
        z_resolution: 0.2
        z_voxels: 32
        max_obstacle_height: 2.0 #2.0 # 3.5 m is > 3.041 meters (max truck height)
        min_obstacle_height: 0.0 # IGNORING GROUND AS OBSTACLE AND SMALL THING UNDER 0.5 Meters.
        mark_threshold: 0
        observation_sources: fused_scan #outside_truck_scan  #real_kinect_sensor/scan
        # outside_truck_scan:
        #   topic: /outside_truck_scan #/real_kinect_sensor/scan
        #   max_obstacle_height: 2.0
        #   clearing: True
        #   marking: True
        #   data_type: "LaserScan"
        #   raytrace_max_range: 50.0 # Half of maximum lidar data range
        #   raytrace_min_range: 0.0 #Lidar is detecting the cabin itself as obstacle and populating costmap around the robot set param >0.0
        #   obstacle_max_range: 50.0 # Half of maximum lidar data range
        #   obstacle_min_range: 0.5
        fused_scan:
          topic: /fused_scan #/real_kinect_sensor/scan
          max_obstacle_height: 2.0
          clearing: True
          marking: True
          data_type: "LaserScan"
          raytrace_max_range: 50.0 # Half of maximum lidar data range
          raytrace_min_range: 0.0 #Lidar is detecting the cabin itself as obstacle and populating costmap around the robot set param >0.0
          obstacle_max_range: 50.0 # Half of maximum lidar data range
          obstacle_min_range: 1.0 # > 0.0 avoid that lidar detect truck as obstacle  #Lidar is detecting the cabin itself as obstacle and populating costmap around the robot set param >0.0
        # right_scan:
        #   topic: /right_scan
        #   max_obstacle_height: 2.0
        #   clearing: True
        #   marking: True
        #   data_type: "LaserScan"
        #   raytrace_max_range: 50.0 # Half of maximum lidar data range
        #   raytrace_min_range: 0.0
        #   obstacle_max_range: 50.0 # Half of maximum lidar data range
        #   obstacle_min_range: 0.0
      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:
      unknown_cost_value: 255 # slightly less than 255 to be more explorative
      lethal_cost_threshold: 100
      #Added above to improve slam exploration
      update_frequency: 1.0
      publish_frequency: 1.0
      global_frame: map
      robot_base_frame: base_link
      use_sim_time: True
      footprint:  "[[-4.8025, -1.739], [4.8025, -1.739], [4.8025, 1.739], [-4.8025, 1.739]]"
      #robot_radius: 0.22
      resolution: 0.2
      track_unknown_space: true
      plugins: ["static_layer", "obstacle_layer", "inflation_layer"]
      obstacle_layer:
        plugin: "nav2_costmap_2d::ObstacleLayer"
        enabled: True
        observation_sources: fused_scan #outside_truck_scan #left_scan real_kinect_sensor/scan
        outside_truck_scan:
          topic: /fused_scan
          max_obstacle_height: 2.0
          clearing: True
          marking: True
          data_type: "LaserScan"
          raytrace_max_range: 100.0
          raytrace_min_range: 0.0
          obstacle_max_range: 25.0
          obstacle_min_range: 1.0
        # fused_scan:
        #   topic: /fused_scan
        #   max_obstacle_height: 2.0
        #   clearing: True
        #   marking: True
        #   data_type: "LaserScan"
        #   raytrace_max_range: 100.0
        #   raytrace_min_range: 0.0
        #   obstacle_max_range: 25.0
        #   obstacle_min_range: 1.0
      static_layer:
        plugin: "nav2_costmap_2d::StaticLayer"
        map_subscribe_transient_local: True
      inflation_layer:
        plugin: "nav2_costmap_2d::InflationLayer"
        cost_scaling_factor: 1.0 #3.0
        inflation_radius: 0.5 #2.0 #0.55
      always_send_full_costmap: True
  global_costmap_client:
    ros__parameters:
      use_sim_time: True
  global_costmap_rclcpp_node:
    ros__parameters:
      use_sim_time: True

map_server:
  ros__parameters:
    use_sim_time: True
    yaml_filename: "infinite_map.yaml"

map_saver:
  ros__parameters:
    use_sim_time: True
    save_map_timeout: 5.0
    free_thresh_default: 0.25
    occupied_thresh_default: 0.65
    map_subscribe_transient_local: True

planner_server:
  ros__parameters:
    expected_planner_frequency: 20.0
    use_sim_time: True
    planner_plugins: ["GridBased"]

    GridBased:
      plugin:  "nav2_smac_planner/SmacPlannerHybrid" #"nav2_smac_planner/SmacPlannerLattice"
      downsample_costmap: false
      downsampling_factor: 1
      tolerance: 1.0 #0.5 #0.25 # Adjust based on how much error you can tolerate in the planned path
      allow_unknown: true
      cost_scaling_factor: 0.9
      neutral_cost: 50
      max_iterations: 1000000
      max_on_approach_iterations: 1000
      max_planning_time: 10.0  # If you find planning takes too long, you might want to lower this
      motion_model_for_search:  "DUBIN" #"REEDS_SHEPP"
      angle_quantization_bins: 72
      analytic_expansion_ratio: 3.5
      analytic_expansion_max_length: 3.0
      #The parameter below creates a curve shape of the end of planner forcing a curved
      minimum_turning_radius: 0.00001 # Adjust based on your robot's actual turning radius
      reverse_penalty: 2.0
      change_penalty: 0.0
      non_straight_penalty: 1.2
      cost_penalty: 2.0
      retrospective_penalty: 0.015
      lookup_table_size: 20.0
      cache_obstacle_heuristic: false
      smooth_path: True # If your robot can handle sharp turns, you might not need path smoothing
      costmap:
        resolution: 0.75 #0.2
        #width: 25 #150
        #height: 25 #150
        #radius: 0.22
        footprint:  "[[-4.8025, -1.739], [4.8025, -1.739], [4.8025, 1.739], [-4.8025, 1.739]]"


      smoother:
        max_iterations: 2000 #1000
        w_smooth: 1.0 #0.5 # 0.3 # Adjust based on how much smoothing you want (higher value means more smoothing)
        w_data: 1.0 #0.5 #0.2 # Adjust based on how closely you want the smoothed path to adhere to the original path
        tolerance: 1.0e-10
        do_refinement: true
        refinement_num: 10 #2

planner_server_rclcpp_node:
  ros__parameters:
    use_sim_time: True

recoveries_server:
  ros__parameters:
    costmap_topic: local_costmap/costmap_raw
    footprint_topic: local_costmap/published_footprint
    cycle_frequency: 10.0
    recovery_plugins: ["spin", "backup", "wait"]
    spin:
      plugin: "nav2_recoveries/Spin"
    backup:
      plugin: "nav2_recoveries/BackUp"
    wait:
      plugin: "nav2_recoveries/Wait"
    global_frame: odom
    robot_base_frame: base_link
    transform_timeout: 0.1
    use_sim_time: true
    simulate_ahead_time: 2.0
    max_rotational_vel: 1.0
    min_rotational_vel: 0.4
    rotational_acc_lim: 3.2

robot_state_publisher:
  ros__parameters:
    use_sim_time: True

waypoint_follower:
  ros__parameters:
    loop_rate: 20
    stop_on_failure: false
    waypoint_task_executor_plugin: "wait_at_waypoint"
    wait_at_waypoint:
      plugin: "nav2_waypoint_follower::WaitAtWaypoint"
      enabled: True
      waypoint_pause_duration: 200