Mapping with SLAM Toolbox and EasyNav

This HowTo shows how to perform mapping and navigation with SLAM Toolbox and EasyNavigation (EasyNav). It assumes that the environment has already been mapped and that you will now configure and run EasyNav to navigate using the generated map.

Setup

Before starting, ensure that:

1. You have completed the installation steps in Build & Install.

2. You have cloned and built the following repositories in your workspace:

   • EasyNavigation

   • easynav_plugins

   • easynav_playground_kobuki (for simulation)

   • easynav_indoor_testcase (for maps and parameter examples)

3. Your workspace is sourced:

   cd ~/ros/ros2/easynav_ws
   source install/setup.bash
   

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Mapping and Preparation

If you have not yet created a map, follow the steps in Mapping with the Costmap Stack. Once the environment is mapped, save the resulting map files (YAML + image) in the directory of any package in your workspace — for example, inside easynav_indoor_testcase/maps.

You can later reference this map using the parameters package and map_path_file in your configuration file. (Alternatively, you may use an absolute path with map_path_file alone.)

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Creating a Parameter File

In this example, we will use:

• The SeReST controller for motion control.

• The AMCL localizer for probabilistic localization.

• The Simple Maps Manager to load the map representation.

Below is a minimal configuration that allows a simulated robot to navigate in a mapped environment.

controller_node:
  ros__parameters:
    use_sim_time: true
    controller_types: [serest]
    serest:
      rt_freq: 30.0
      plugin: easynav_serest_controller/SerestController
      allow_reverse: true
      max_linear_speed: 0.8
      max_angular_speed: 1.2
      v_progress_min: 0.08
      k_s_share_max: 0.5
      k_theta: 2.5
      k_y: 1.5
      goal_pos_tol: 0.1
      goal_yaw_tol_deg: 6.0
      slow_radius: 0.80
      slow_min_speed: 0.02
      final_align_k: 2.5
      final_align_wmax: 0.8
      corner_guard_enable: true
      corner_gain_ey: 1.8
      corner_gain_eth: 0.7
      corner_gain_kappa: 0.4
      corner_min_alpha: 0.35
      corner_boost_omega: 1.0
      a_lat_soft: 0.9
      apex_ey_des: 0.05

localizer_node:
  ros__parameters:
    use_sim_time: true
    localizer_types: [simple]
    simple:
      rt_freq: 50.0
      freq: 5.0
      reseed_freq: 1.0
      plugin: easynav_simple_localizer/AMCLLocalizer
      num_particles: 100
      noise_translation: 0.05
      noise_rotation: 0.1
      noise_translation_to_rotation: 0.1
      initial_pose:
        x: 0.0
        y: 0.0
        yaw: 0.0
        std_dev_xy: 0.1
        std_dev_yaw: 0.01

maps_manager_node:
  ros__parameters:
    use_sim_time: true
    map_types: [simple]
    simple:
      freq: 10.0
      plugin: easynav_simple_maps_manager/SimpleMapsManager
      package: easynav_indoor_testcase
      map_path_file: maps/home.yaml

planner_node:
  ros__parameters:
    use_sim_time: true
    planner_types: [simple]
    simple:
      freq: 0.5
      plugin: easynav_simple_planner/SimplePlanner
      robot_radius: 0.25

sensors_node:
  ros__parameters:
    use_sim_time: true
    forget_time: 0.5
    sensors: [laser1]
    perception_default_frame: odom
    laser1:
      topic: scan_raw
      type: sensor_msgs/msg/LaserScan
      group: points

system_node:
  ros__parameters:
    use_sim_time: true
    position_tolerance: 0.3
    angle_tolerance: 0.15

—

Running the Simulation

1. Launch the simulator. You can disable the Gazebo GUI to save resources:

   ros2 launch easynav_playground_kobuki playground_kobuki.launch.py gui:=false
   

2. Launch RViz2 in a new terminal:

   ros2 run rviz2 rviz2 --ros-args -p use_sim_time:=true
   

3. Start EasyNav using your parameter file:

   ros2 run easynav_system system_main \
      --ros-args --params-file ~/ros/ros2/easynav_ws/src/easynav_indoor_testcase/robots_params/simple.serest_params.yaml
   

   (You can also create a dedicated launcher file for convenience.)

4. In RViz2, use the “2D Goal Pose” tool to send navigation goals. The robot should begin navigating autonomously along collision-free paths.

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Notes

• Ensure that the map_path_file path and package name correspond to your actual map.

• The Simple Stack is suitable for 2D navigation with binary occupancy grids; for graded cost-based navigation, consider switching to the Costmap Stack (Mapping with the Costmap Stack).

• If navigation oscillates or stalls, verify that the controller gains (k_theta, k_y) and speed limits are consistent with your robot’s maximum velocities.