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[skip ci] publish latest
Signed-off-by: fmrico <fmrico@gmail.com>
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‎_images/base_icreate.jpg‎

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‎_images/rpi_icreate.jpg‎

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‎_sources/index.rst.txt‎

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|LPN|
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*****
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.. raw:: html
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<h1 align="center">
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<div>
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<div style="position: relative; padding-bottom: 0%; overflow: hidden; max-width: 100%; height: auto;">
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<iframe width="450" height="300" src="https://www.youtube.com/embed/MssaLixuv2g?autoplay=1&mute=1" frameborder="1" allowfullscreen></iframe>
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<iframe width="450" height="300" src="https://www.youtube.com/embed/mxivTYNY1yY?autoplay=1&mute=1" frameborder="1" allowfullscreen></iframe>
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</div>
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</div>
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</h1>
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Overview
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########
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‎_sources/tutorials/easynav_costmap_stack/index.rst.txt‎

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‎_sources/tutorials/easynav_costmap_stack/mapping.rst.txt‎

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.. mapping:
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Mapping with the Costmap Stack
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------------------------------
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The mapping workflow with the ``easynav_costmap_stack`` mirrors the one used in the Simple Stack.
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For background and step-by-step context, see :doc:`the Simple Stack Mapping tutorial <../easynav_simple_stack/mapping>`.
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The main difference is that here the environment is represented internally as a graded **Costmap2D** instead of a
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binary occupancy grid.
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Overview
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^^^^^^^^
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1. **Generate a map** (e.g., using a SLAM solution). The output should be a **YAML + image** pair
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(``.yaml`` + ``.pgm/.png``) describing resolution, origin and free/occupied thresholds.
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2. **Place the map files** inside a package in your workspace. The Costmap Maps Manager will later load it
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using the pair of parameters ``package`` and ``map_path_file`` (you can also provide an absolute path).
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3. **Prepare an EasyNav parameters file**. In this tutorial we will use *dummy* plugins for controller,
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planner and localizer, and the **Costmap Maps Manager** to load and publish the map. This is enough to
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validate that the costmap is properly loaded and visualized.
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Example parameters
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^^^^^^^^^^^^^^^^^^
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Below is a minimal working configuration you can use to verify mapping. It mirrors the structure of the Simple Stack
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example but uses the Costmap-based maps manager. You may replace ``my_maps_pkg`` and the YAML path with your own.
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.. code-block:: yaml
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controller_node:
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ros__parameters:
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use_sim_time: true
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controller_types: [dummy]
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dummy:
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rt_freq: 30.0
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plugin: easynav_controller/DummyController
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cycle_time_nort: 0.01
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cycle_time_rt: 0.001
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localizer_node:
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ros__parameters:
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use_sim_time: true
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localizer_types: [dummy]
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dummy:
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rt_freq: 50.0
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freq: 5.0
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reseed_freq: 0.1
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plugin: easynav_localizer/DummyLocalizer
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cycle_time_nort: 0.01
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cycle_time_rt: 0.001
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maps_manager_node:
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ros__parameters:
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use_sim_time: true
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map_types: [costmap]
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costmap:
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freq: 10.0
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plugin: easynav_costmap_maps_manager/CostmapMapsManager
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package: my_maps_pkg
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map_path_file: maps/office.yaml
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planner_node:
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ros__parameters:
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use_sim_time: true
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planner_types: [dummy]
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dummy:
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freq: 1.0
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plugin: easynav_planner/DummyPlanner
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cycle_time_nort: 0.2
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cycle_time_rt: 0.001
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sensors_node:
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ros__parameters:
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use_sim_time: true
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forget_time: 0.5
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system_node:
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ros__parameters:
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use_sim_time: true
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position_tolerance: 0.1
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angle_tolerance: 0.05
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Running and visualizing
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^^^^^^^^^^^^^^^^^^^^^^^
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1. Launch your simulator (or a static map server) and start EasyNav with the parameter file above.
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2. Open ``rviz2`` and add an *OccupancyGrid* display for the topic
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``maps_manager_node/<plugin_name>/map`` (static) or ``maps_manager_node/<plugin_name>/dynamic_map`` (dynamic).
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You should see the costmap as a grayscale image where darker values denote higher traversal cost.
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Saving maps (SLAM Toolbox vs. Maps Manager)
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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The Costmap Maps Manager reads and writes maps using the **same YAML + image format** as MoveBase/Nav2.
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That means you do *not* need to rely on the manager's internal save path if you are producing the map with SLAM Toolbox.
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- **Option A (Maps Manager service):** The manager exposes a ``savemap`` service at
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``maps_manager_node/<plugin_name>/savemap`` which saves its current static map to the configured path.
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- **Option B (Recommended with SLAM Toolbox):** Call the SLAM Toolbox service
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``/slam_toolbox/save_map`` (service type ``slam_toolbox/srv/SaveMap``) directly. This will write the
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YAML + image pair in the standard format that the Costmap Maps Manager can later load with
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``package`` + ``map_path_file``.
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.. note::
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This tutorial is analogous to :doc:`../easynav_simple_stack/mapping`. The only conceptual change is the
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internal map representation (``Costmap2D`` with values 0–255 and obstacle inflation support) which allows
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subsequent components (planner/controller) to leverage graded costs instead of a hard free/occupied dichotomy.

‎_sources/tutorials/easynav_costmap_stack/navigating.rst.txt‎

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.. navigating:
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Mapping with SLAM Toolbox and EasyNav
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-------------------------------------
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.. raw:: html
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<h1 align="center">
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<div>
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<div style="position: relative; padding-bottom: 0%; overflow: hidden; max-width: 100%; height: auto;">
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<iframe width="450" height="300" src="https://www.youtube.com/embed/n1vDA4ZeG6M" frameborder="1" allowfullscreen></iframe>
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</div>
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</div>
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</h1>
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Once the environment has been mapped, save the ``.map`` file in the directory of any package in your workspace.
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This will be required because we will later reference it using the package name and relative path.
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(Optionally, you can provide the absolute path through the parameter ``map_path_file``).
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Next, create a parameter file for navigation.
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In this example we will use the **SeReST controller**, **AMCL** for robot localization, and specify that the ``maps_manager`` is an instance of ``easynav_simple_maps_manager/SimpleMapsManager``.
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In the corresponding section we define where the map is located and configure the laser as the sensor to be used:
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.. code-block:: yaml
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controller_node:
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ros__parameters:
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use_sim_time: true
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controller_types: [serest]
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serest:
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rt_freq: 30.0
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plugin: easynav_serest_controller/SerestController
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allow_reverse: true
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max_linear_speed: 0.8
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max_angular_speed: 1.2
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v_progress_min: 0.08
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k_s_share_max: 0.5
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k_theta: 2.5
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k_y: 1.5
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goal_pos_tol: 0.1
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goal_yaw_tol_deg: 6.0
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slow_radius: 0.80
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slow_min_speed: 0.02
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final_align_k: 2.5
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final_align_wmax: 0.8
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corner_guard_enable: true
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corner_gain_ey: 1.8
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corner_gain_eth: 0.7
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corner_gain_kappa: 0.4
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corner_min_alpha: 0.35
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corner_boost_omega: 1.0
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a_lat_soft: 0.9
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apex_ey_des: 0.05
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localizer_node:
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ros__parameters:
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use_sim_time: true
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localizer_types: [simple]
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simple:
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rt_freq: 50.0
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freq: 5.0
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reseed_freq: 1.0
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plugin: easynav_simple_localizer/AMCLLocalizer
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num_particles: 100
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noise_translation: 0.05
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noise_rotation: 0.1
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noise_translation_to_rotation: 0.1
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initial_pose:
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x: 0.0
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y: 0.0
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yaw: 0.0
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std_dev_xy: 0.1
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std_dev_yaw: 0.01
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maps_manager_node:
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ros__parameters:
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use_sim_time: true
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map_types: [simple]
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simple:
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freq: 10.0
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plugin: easynav_simple_maps_manager/SimpleMapsManager
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package: easynav_indoor_testcase
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map_path_file: maps/home.map
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planner_node:
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ros__parameters:
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use_sim_time: true
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planner_types: [simple]
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simple:
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freq: 0.5
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plugin: easynav_simple_planner/SimplePlanner
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robot_radius: 0.25
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sensors_node:
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ros__parameters:
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use_sim_time: true
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forget_time: 0.5
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sensors: [laser1]
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perception_default_frame: odom
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laser1:
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topic: scan_raw
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type: sensor_msgs/msg/LaserScan
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group: points
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system_node:
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ros__parameters:
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use_sim_time: true
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position_tolerance: 0.3
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angle_tolerance: 0.15
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In one terminal, launch the simulator.
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You can disable the GUI to save resources if needed:
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.. code-block:: bash
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ros2 launch easynav_playground_kobuki playground_kobuki.launch.py gui:=false
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In a second terminal, launch ``rviz``:
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.. code-block:: bash
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ros2 run rviz2 rviz2 --ros-args -p use_sim_time:=true
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Finally, in a third terminal, start **EasyNav** and specify the parameter file.
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(Optionally, you can also create a launcher for convenience):
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.. code-block:: bash
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ros2 run easynav_system system_main \
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--ros-args --params-file /home/fmrico/ros/ros2/easynav_ws/src/easynav_indoor_testcase/robots_params/simple.serest_params.yaml
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At this point, you can use the **“2D Goal Pose”** button in ``rviz`` to send target positions for the robot to navigate to.

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