rskill-nav2-navigate-to-pose

OpenRAL rSkill — wraps the upstream nav2_msgs/action/NavigateToPose action server as an OpenRAL rSkill so the Reasoner can dispatch mobile-base navigation through the same ExecuteSkill path used by VLA skills. Result-only mode — Nav2's behaviour tree publishes /cmd_vel directly to the base controller; no Action chunk flows through OpenRAL's safety supervisor.

This package uses kind: ros_action (see ADR-0024) with ros_integration.result_trajectory_field: null to put the ROSActionRskill adapter into result-only mode: it sends the goal, awaits the action result, and raises ROSRskillGoalSatisfied on success. Compare with the sibling rskill-moveit-joints skill, which sets result_trajectory_field and replays a joint trajectory one waypoint at a time.

What this skill does

Navigates the mobile base to a fixed geometry_msgs/PoseStamped target in the map frame via Nav2's NavigateToPose action. The default goal points at the map origin; override ros_integration.default_goal_json in a per-deployment copy for real targets.

Field	Value
Actions	`navigate`
Objects	none
Scenes	`indoor`
Embodiment	mobile-manipulator and similar mobile-base embodiments

How it works

ROSActionRskill is a thin rSkillBase shim around an ActionClient:

_configure_impl lazy-imports nav2_msgs.action.NavigateToPose, opens an ActionClient on /navigate_to_pose from the RskillRunnerNode-supplied node handle, and parses ros_integration.default_goal_json once.
On the first _step_impl(world_state) call the adapter sends the goal, polls the goal-accept + result futures while the host node's main rclpy spin services callbacks, and — because result_trajectory_field is None — raises ROSRskillGoalSatisfied immediately on success. The runner catches it specifically and closes the ExecuteSkill goal with success=True.

Observation → action contract (result-only mode)

Direction	Key	Shape	Notes
in	`world_state.joint_state`	unused	Nav2 consumes its own sensor topics (laser, odom, camera)
out	none via OpenRAL	—	Nav2's behaviour tree publishes `/cmd_vel` directly to the base controller

Safety implication. No ActionChunk is published on /openral/candidate_action, so the OpenRAL safety supervisor does NOT see Nav2's velocity commands. Collision avoidance relies entirely on Nav2's costmap + behaviour tree. The follow-up that brings velocity streams under the supervisor's envelope is tracked in ADR-0024's §Out-of-scope and depends on (a) a mobile-base HAL declaring body_twist in supported_control_modes (none exist in-tree today), and (b) a velocity / jerk envelope landing in the supervisor (it currently checks per-joint position only).

How it was trained / Upstream provenance

Nothing is trained — this rSkill wraps the upstream Nav2 stack.

Field	Value
Upstream	`nav2_msgs/action/NavigateToPose` (Apache-2.0)
Planner library	Nav2 (Apache-2.0)
Costmap / behaviour tree	Nav2's own subsystems — see Nav2 docs
Wrapped artefact	rSkill manifest + README — no weights

Supported robots / embodiments

Robot	Embodiment tag	Status	Notes
Panda Mobile	`panda_mobile`	experimental	no HAL accepting `body_twist` ships in-tree yet; resolution depends on the deployment wiring its own mobile-base HAL or running Nav2's controllers against a sim
Generic mobile-manipulator	`mobile_manipulator`	experimental	union tag — palette filter only

A real mobile-base HAL (Turtlebot 4, Clearpath Jackal, etc.) is the prerequisite for full end-to-end execution — tracked as a separate issue.

Sensors required / Observation contract

This skill consumes nothing through OpenRAL's sensor pipeline. Nav2's own subscriptions handle:

Source	Topic	Why Nav2 needs it
Laser scan	`/scan` (or per-deployment remap)	Costmap obstacle layer
Odometry	`/odom`	Localisation + behaviour-tree feedback
TF	`/tf`, `/tf_static`	Resolve goal pose in the `map` frame
Map	`/map` (or AMCL initial pose)	Global planner

If your deployment uses a non-default topic remap, surface it on the Nav2 launch — the wrapped action's contract is intact.

Manifest summary

Field	Value
`name`	`OpenRAL/rskill-nav2-navigate-to-pose`
`version`	`0.1.0`
`license`	`apache-2.0`
`kind`	`ros_action`
`role`	`s1`
`actions`	`[navigate]`
`chunk_size`	`1` (schema-enforced for `kind: ros_action`)
`latency_budget.per_chunk_ms`	`60000` (navigation is long-horizon; the adapter waits ×5 of this on the action result)
`ros_integration.package`	`nav2_msgs`
`ros_integration.interface_type`	`NavigateToPose`
`ros_integration.interface_name`	`/navigate_to_pose`
`ros_integration.result_trajectory_field`	omitted → result-only mode
`commercial_use_allowed`	`true` (apache-2.0)

Full schema: openral_core.schemas.RSkillManifest.

Quick start

from openral_rskill.loader import rSkill
pkg = rSkill.from_yaml("rskills/rskill-nav2-navigate-to-pose/rskill.yaml")
print(pkg.manifest.name, pkg.manifest.kind, pkg.manifest.ros_integration.interface_name)

End-to-end, with a real Nav2 launch up (e.g. against a Gazebo / Turtlebot4 sim):

# 1. Bring up Nav2 for your mobile-base sim or robot
ros2 launch nav2_bringup tb4_simulation_launch.py

# 2. Bring up the OpenRAL runner against that embodiment
ros2 launch openral_rskill_ros skill_runner.launch.py robot:=panda_mobile

# 3. From the Reasoner (or by hand), dispatch the goal:
ros2 action send_goal /openral/execute_skill openral_msgs/action/ExecuteSkill \
    "{rskill_id: 'OpenRAL/rskill-nav2-navigate-to-pose', deadline_s: 120.0, prompt: 'go to map origin'}"

Limitations / Roadmap

Velocity stream bypasses the OpenRAL safety supervisor. Nav2 publishes /cmd_vel directly. See ADR-0024 §Out-of-scope.
Goal hard-coded in the manifest. v1 ships one goal per manifest; structured-prompt support is the next ADR.
No mobile-base HAL in-tree. Until one lands, the skill resolves only inside deployments that ship their own mobile-base wiring.

License

The rSkill package itself (this manifest + README) is Apache-2.0. The wrapped Nav2 code (nav2_msgs IDL, navigation2 planners) is Apache-2.0 and lives outside this repository — installed via ros-${ROS_DISTRO}-nav2-bringup. Per ADR-0012 both postures are commercial-use-permissive.

OpenRAL
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rskill-nav2-navigate-to-pose