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asr_psm package from asr_psm repo

asr_psm

Package Summary

Tags No category tags.
Version 1.0.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/asr-ros/asr_psm.git
VCS Type git
VCS Version master
Last Updated 2019-11-14
Dev Status UNMAINTAINED
CI status No Continuous Integration
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

This package contains a system to recognize scenes called the Probabilistic Scene Model (PSM). It uses objects and relative poses (relations) between the objects. The realations can be dynamic and each object can be a reference object. The system consists of a training subsystem that trains new scenes and a scene inference subsystem that calculates scene probabilities of previously trained scenes.

Additional Links

No additional links.

Maintainers

  • Meißner Pascal

Authors

  • Braun Kai, Gehrung Joachim, Heizmann Heinrich, Meißner Pascal

asr_psm

Documentation: http://wiki.ros.org/asr_psm

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Launch files

  • launch/combinatorial_learner.launch
    • Launches the learner for probabilistic scene models. This launch file is specifically designed for launching the learner to use combinatorial optimization to generate object relation graphs. Incoming AsrScenGraph messages are collected and being used for model learning.
  • launch/inference.launch
    • Launches the inference engine for probabilistic scene recognition. Incoming AsrObject messages are being processed and the results used for scene recognition.
  • launch/learner.launch
    • Launches the learner for probabilistic scene models. Incoming AsrScenGraph messages are collected and being used for model learning.
  • launch/inf_screen.launch
    • Launches the inference engine for probabilistic scene recognition. Incoming AsrObject messages are being processed and the results used for scene recognition.
  • launch/validator.launch
    • Launches the validator, which tests the given model against the given test sets and counts false recognitions and runtime. Calculates some statistical values (average of runtime and false recognitions, ratio of false recognition against number of sets). Writes the results as csv to the given file
  • launch/go.launch
    • Launches camera and recognition system.
  • launch/start_scene_graph_generation.launch
    • Please take into account that recognition_for_grasping does not set AsrObject identifier yet. Therefore all measured object locations of the same object type are accumulated into one trajectory even for multiple objects.
  • launch/start_cameras.launch
    • Launches the whole system for probabilistic scene recognition.

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged asr_psm at Robotics Stack Exchange

asr_psm package from asr_psm repo

asr_psm

Package Summary

Tags No category tags.
Version 1.0.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/asr-ros/asr_psm.git
VCS Type git
VCS Version master
Last Updated 2019-11-14
Dev Status UNMAINTAINED
CI status No Continuous Integration
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

This package contains a system to recognize scenes called the Probabilistic Scene Model (PSM). It uses objects and relative poses (relations) between the objects. The realations can be dynamic and each object can be a reference object. The system consists of a training subsystem that trains new scenes and a scene inference subsystem that calculates scene probabilities of previously trained scenes.

Additional Links

No additional links.

Maintainers

  • Meißner Pascal

Authors

  • Braun Kai, Gehrung Joachim, Heizmann Heinrich, Meißner Pascal

asr_psm

Documentation: http://wiki.ros.org/asr_psm

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Launch files

  • launch/combinatorial_learner.launch
    • Launches the learner for probabilistic scene models. This launch file is specifically designed for launching the learner to use combinatorial optimization to generate object relation graphs. Incoming AsrScenGraph messages are collected and being used for model learning.
  • launch/inference.launch
    • Launches the inference engine for probabilistic scene recognition. Incoming AsrObject messages are being processed and the results used for scene recognition.
  • launch/learner.launch
    • Launches the learner for probabilistic scene models. Incoming AsrScenGraph messages are collected and being used for model learning.
  • launch/inf_screen.launch
    • Launches the inference engine for probabilistic scene recognition. Incoming AsrObject messages are being processed and the results used for scene recognition.
  • launch/validator.launch
    • Launches the validator, which tests the given model against the given test sets and counts false recognitions and runtime. Calculates some statistical values (average of runtime and false recognitions, ratio of false recognition against number of sets). Writes the results as csv to the given file
  • launch/go.launch
    • Launches camera and recognition system.
  • launch/start_scene_graph_generation.launch
    • Please take into account that recognition_for_grasping does not set AsrObject identifier yet. Therefore all measured object locations of the same object type are accumulated into one trajectory even for multiple objects.
  • launch/start_cameras.launch
    • Launches the whole system for probabilistic scene recognition.

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged asr_psm at Robotics Stack Exchange