[Documentation] [TitleIndex] [WordIndex

Package Summary

This package includes the algorithmic link between object pose prediction and scene recognition, both based on ISM trees. While it only refers to other packages with respect to the aforementioned functionalities, it includes the algorithms realizing Scene Model Sampling. E.g., it provides a (service-based) interface for the scene recognition, including an ASR-optimized visualization of ISM trees. The reason for linking scene recognition and object pose prediction within a package instead of message passing, is the size and number of scene recognition results occurring.

Package Summary

This package includes the algorithmic link between object pose prediction and scene recognition, both based on ISM trees. While it only refers to other packages with respect to the aforementioned functionalities, it includes the algorithms realizing Scene Model Sampling. E.g., it provides a (service-based) interface for the scene recognition, including an ASR-optimized visualization of ISM trees. The reason for linking scene recognition and object pose prediction within a package instead of message passing, is the size and number of scene recognition results occurring.

Logo-white-medium.jpg

Description

This package includes the algorithmic link between object pose prediction and scene recognition, both based on ISM trees. While it only refers to other packages with respect to the aforementioned functionalities, it includes the algorithms realizing Scene Model Sampling. E.g., it provides a (service-based) interface for the scene recognition, including an ASR-optimized visualization of ISM trees. The reason for linking scene recognition and object pose prediction within a package instead of message passing, is the size and number of scene recognition results occurring.

Functionality

This package is the connection between pose prediction and scene recognition. It provides several services for controlling purpose. Its main parts are:

The following picture illustrates the process of the package:

szene_partikelfilter.png

Initially, the objects that were found are used to compute which scenes could be present (scene recognition). In the second step, these scenes are rated by their probability. In the last step, pose predictions for the missing objects are generated by resampling the rated results with importance sampling.

Usage

You need the ISM package for the scene detection and a source for AsrObjects.

Needed packages

Start system

Before you can start the rp_ism_node, you have to launch the world_model:

roslaunch asr_world_model world_model.launch

All functionality goes to one ros-node: the rp_ism_node. To launch it simply call:

roslaunch asr_recognizer_prediction_ism rp_ism_node.launch

ROS Nodes

Published Topics

The topics that the package publishes are only meant for the visualization. Those topics are:

Parameters

You have to set some parameters in:

param/scene_recognition.yaml

param/pose_prediction.yaml

Services

Tutorials

AsrRecognizerPredictionIsmGeneralTutorial


2020-09-19 12:34