easynav_costmap_planner

Description

A planner plugin implementing a standard A* path planner over a Costmap2D representation. It reads the dynamic costmap, goal list, and robot pose from NavState and publishes a computed path as a nav_msgs/Path message.

Authors and Maintainers

• Authors: Intelligent Robotics Lab
• Maintainers: Francisco Martín Rico fmrico@gmail.com

Supported ROS 2 Distributions

| Distribution | Status | |—|—| | humble | | | jazzy | | | kilted | | | rolling | |

Plugin (pluginlib)

• Plugin Name: easynav_costmap_planner/CostmapPlanner
• Type: easynav::CostmapPlanner
• Base Class: easynav::PlannerMethodBase
• Library: easynav_costmap_planner
• Description: A default Costmap2D-based A* path planner implementation.

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Parameters

All parameters are declared under the plugin namespace, i.e., /<node_fqn>/easynav_costmap_planner/CostmapPlanner/....

Name	Type	Default	Description
<plugin>.cost_factor	double	2.0	Scaling factor applied to costmap cell values to compute traversal costs. Higher values make high-cost cells much less attractive.
<plugin>.inflation_penalty	double	5.0	Extra penalty added to inflated/near-obstacle cells to push paths away from obstacles.
<plugin>.heuristic_scale	double	1.0	Scaling factor applied to the A* heuristic term. Controls the trade-off between following the cheapest route vs. going more directly.
<plugin>.continuous_replan	bool	true	If true, re-plans continuously as the map/goal changes; if false, plans once per request.

Effect of cost_factor

The planner uses a per-step traversal cost:

\[g_{\text{new}} = g_{\text{current}} + \text{step\_cost} \cdot \left(1 + \text{cost\_factor} \cdot \frac{\text{cell\_cost}}{\text{LETHAL\_OBSTACLE}}\right)\]

• Low cost_factor (e.g. 1–2):
  • Cell cost has a modest influence; the planner is closer to a pure geometric shortest-path search.
  • Paths may cross moderately expensive regions if that keeps distance short.
• High cost_factor (e.g. 5–10+):
  • High-cost cells become very unattractive, so the planner strongly prefers low-cost corridors (e.g. routes or low-inflation areas), even if they are longer.
  • Useful when combined with modules that encode preferences as higher costs (such as route managers).

Effect of heuristic_scale

The A* priority is:

\[f = g + h, \quad h = \text{heuristic\_scale} \cdot d_{\text{cells}}(\text{current}, \text{goal})\]

where $d_{\text{cells}}$ is the Euclidean distance in cell indices (not metric distance, but proportional).

• Decrease heuristic_scale (< 1.0):
  • The heuristic term becomes weaker, and A* behaves more like Dijkstra.
  • The search explores more alternatives and is guided more strictly by the true accumulated cost $g$.
  • This usually makes the planner follow high-cost penalties (e.g. for leaving a route) more faithfully, at the expense of more computation.
• Increase heuristic_scale (> 1.0):
  • The heuristic term dominates more, so the planner prefers geometrically direct paths.
  • It may still avoid extremely high-cost regions if cost_factor is large, but will be more willing to “cut corners” through slightly more expensive zones.

Typical tuning strategy:

• First, adjust cost_factor so that the costmap properly encodes your preferences:
  • Increase it until paths clearly avoid high-cost areas that should be disfavored.
• Then, fine-tune heuristic_scale:
  • Start from 1.0.
  • If the planner still takes shortcuts that ignore cost differences, consider reducing it slightly (e.g. 0.7–0.9).
  • If planning becomes too slow or explores too widely, you can increase it modestly (e.g. 1.2–1.5).

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Interfaces (Topics and Services)

Publications

| Direction | Topic | Type | Purpose | QoS | |—|—|—|—|—| | Publisher | <node_fqn>/<plugin>/path | nav_msgs/msg/Path | Publishes the computed path from start to goal. | depth=10 |

This plugin does not create subscriptions or services directly; it reads inputs via NavState.

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NavState Keys

| Key | Type | Access | Notes | |—|—|—|—| | goals | nav_msgs::msg::Goals | Read | Goal list used as planner targets. | | map.dynamic | Costmap2D | Read | Dynamic costmap used for A* search. | | robot_pose | nav_msgs::msg::Odometry | Read | Current robot pose used as the start position. |

File truncated at 100 lines see the full file

Changelog for package easynav_costmap_planner

0.2.1 (2026-02-27)

• 0.2.0
• GPLv3 -> Apache 2.0
• Documentation was corrected
• Add a base_footprint frame in TFInfo
• Remove C++20/C++23 features and update to new MethodBase interface
• TFInfo in RTTFBuffer
• Refactor to use TFInfo
• Referencing base class if ot void
• Optimize execution
• Cleanup unused headers
• Update sheets
• Contributors: Francisco Martín Rico, Francisco Miguel Moreno, Jose Miguel, José Miguel Guerrero, Juan S. Cely G., Miguel

0.0.2 (2025-10-12)

• Reorganization initial
• Contributors: Francisco Martín Rico