asr_recognizer_prediction_psm repository

Repository Summary

Checkout URI https://github.com/asr-ros/asr_recognizer_prediction_psm.git
VCS Type git
VCS Version master
Last Updated 2020-02-17
Dev Status UNMAINTAINED
CI status No Continuous Integration
Released UNRELEASED
Package Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
asr_recognizer_prediction_psm 1.0.0

README

How to start PSM_NODE (PSM Scene Recognition + Pose Prediction):

How to start psm_node:
roscore
start kinematic chain - roslaunch asr_kinematic_chain_dome transformation_publisher_left.launch
start the server - roslaunch asr_recognizer_prediction_psm psm_node
call the service - roscd asr_recognizer_prediction_psm
python python/psm_node_test.py


Note:

There are no hypothesis generated for the background scene. See the python/psm_node_test.py for an example usage.

What are the parameters of the service call:


asr_msgs/AsrObject[] objects                - input: the list of all oberved objects
---
next_best_view/AttributedPointCloud pose_hypothesis - output: the generated hypothesis












How to start ONLY pose prediciton:
1. start kinematic chain (needed for transformation into target frame eg. /map) - roslaunch kinematic_chain transformation_publishers_left.launch
2. it seems that the kinematic_chain does not contain all transformations. Start asr_flir_ptu_driver - roslaunch asr_flir_ptu_driver ptu_left.launch
3. rosrun asr_recognizer_prediction_psm recognizer_prediction_psm
4. python pyhton/recognizer_prediction_test.py or rosrun asr_recognizer_prediction_psm recognizer_prediction_psm_client 10


What are the parameters of the service call:

string path                     - input: the path to the xml file that contains the scenes (eg. models/breakfast.xml)
string[] scenes                     - input: the name of the scenes. It gerneates hypothesis only for these scenes. 
float32[] scene_probabilities               - input: contains the probability of the scene
uint32 num_votes                    - input: the overall number of hypothesis that should be generated
asr_msgs/AsrObject[] objects                - input: the list of all oberved objects
string base_frame_id                    - input: the base frame to which the observed objects and the hypothesis should be transformed into
---
next_best_view/AttributedPointCloud pose_hypothesis - output: the generated hypothesis



Note:
- the number of scene_probabilities has to be equal to the number of scenes
- the sum of the scene_probabilities should be 1.0, otherwise the number of hypothesis will not be correct
- there has to be at least one observed object
- if there are more than one object observed, the first object in the objects list that occurs in the scene will be treated as reference object


See 
http://i61p109.ira.uka.de/twiki/bin/view/IlcasProjects/PosePredictionPsm
for further documentation.


CONTRIBUTING

No CONTRIBUTING.md found.

Repository Summary

Checkout URI https://github.com/asr-ros/asr_recognizer_prediction_psm.git
VCS Type git
VCS Version master
Last Updated 2020-02-17
Dev Status UNMAINTAINED
CI status No Continuous Integration
Released UNRELEASED
Package Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
asr_recognizer_prediction_psm 1.0.0

README

How to start PSM_NODE (PSM Scene Recognition + Pose Prediction):

How to start psm_node:
roscore
start kinematic chain - roslaunch asr_kinematic_chain_dome transformation_publisher_left.launch
start the server - roslaunch asr_recognizer_prediction_psm psm_node
call the service - roscd asr_recognizer_prediction_psm
python python/psm_node_test.py


Note:

There are no hypothesis generated for the background scene. See the python/psm_node_test.py for an example usage.

What are the parameters of the service call:


asr_msgs/AsrObject[] objects                - input: the list of all oberved objects
---
next_best_view/AttributedPointCloud pose_hypothesis - output: the generated hypothesis












How to start ONLY pose prediciton:
1. start kinematic chain (needed for transformation into target frame eg. /map) - roslaunch kinematic_chain transformation_publishers_left.launch
2. it seems that the kinematic_chain does not contain all transformations. Start asr_flir_ptu_driver - roslaunch asr_flir_ptu_driver ptu_left.launch
3. rosrun asr_recognizer_prediction_psm recognizer_prediction_psm
4. python pyhton/recognizer_prediction_test.py or rosrun asr_recognizer_prediction_psm recognizer_prediction_psm_client 10


What are the parameters of the service call:

string path                     - input: the path to the xml file that contains the scenes (eg. models/breakfast.xml)
string[] scenes                     - input: the name of the scenes. It gerneates hypothesis only for these scenes. 
float32[] scene_probabilities               - input: contains the probability of the scene
uint32 num_votes                    - input: the overall number of hypothesis that should be generated
asr_msgs/AsrObject[] objects                - input: the list of all oberved objects
string base_frame_id                    - input: the base frame to which the observed objects and the hypothesis should be transformed into
---
next_best_view/AttributedPointCloud pose_hypothesis - output: the generated hypothesis



Note:
- the number of scene_probabilities has to be equal to the number of scenes
- the sum of the scene_probabilities should be 1.0, otherwise the number of hypothesis will not be correct
- there has to be at least one observed object
- if there are more than one object observed, the first object in the objects list that occurs in the scene will be treated as reference object


See 
http://i61p109.ira.uka.de/twiki/bin/view/IlcasProjects/PosePredictionPsm
for further documentation.


CONTRIBUTING

No CONTRIBUTING.md found.