robokudo.annotators.icp_pose_refinement
=======================================

.. py:module:: robokudo.annotators.icp_pose_refinement

.. autoapi-nested-parse::

   Pose refinement using iterative closest point (ICP).

   This module provides an annotator for:

   * Refining object pose estimates using ICP
   * Matching against reference point cloud models
   * Supporting multiple initial pose variants
   * Evaluating registration quality

   The module uses:

   * Open3D ICP implementation
   * Point-to-point registration
   * Multiple pose hypotheses
   * PLY model loading
   * Visualization tools

   .. warning::
      Currently limited to refining against a single pre-loaded model.



Classes
-------

.. autoapisummary::

   robokudo.annotators.icp_pose_refinement.ICPPoseRefinementAnnotator


Module Contents
---------------

.. py:class:: ICPPoseRefinementAnnotator(name: str = 'ICPPoseRefinementAnnotator', descriptor: ICPPoseRefinementAnnotator | None = None)

   Bases: :py:obj:`robokudo.annotators.core.ThreadedAnnotator`


   Pose refinement using iterative closest point (ICP).

   This annotator:

   * Refines object pose estimates using ICP
   * Matches against reference point cloud models
   * Evaluates multiple initial pose variants
   * Selects best registration result
   * Creates refined pose annotations

   .. note::
      Point cloud models can be generated from meshes using CloudCompare's
      "Sample points on a mesh" feature.

   .. warning::
      Currently limited to refining against a single pre-loaded model.


   .. py:class:: Descriptor

      Bases: :py:obj:`robokudo.annotators.core.BaseAnnotator.Descriptor`


      Configuration descriptor for ICP refinement.


      .. py:class:: Parameters

         Parameters for configuring model loading.


         .. py:attribute:: ros_pkg_path
            :type:  typing_extensions.Optional[str]
            :value: None


            If set, use use data_path as a relative path to self.ros_pkg_path



         .. py:attribute:: data_path
            :type:  typing_extensions.Optional[str]
            :value: None


            Relative Path to the folder containing the models




      .. py:attribute:: parameters



   .. py:attribute:: class_name_to_ply_model


   .. py:method:: get_model_path(class_name: str = '') -> typing_extensions.Optional[pathlib.Path]

      Get path to PLY model file.

      Resolves model path using:

      * ROS package path if provided
      * Direct data path otherwise

      :param class_name: Name of object class to load model for
      :return: Path to PLY file or None if not found



   .. py:method:: compute() -> py_trees.common.Status

      Process object hypotheses and refine poses.

      The method:

      * Loads point cloud and object hypotheses
      * For each hypothesis with pose:
        * Creates initial pose variants
        * Performs ICP registration for each variant
        * Selects best registration result
        * Creates refined pose annotation
        * Generates visualization markers

      :return: SUCCESS after processing, even if annotator deactivated