Situational Graphs - Reasoning

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro jazzy showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro kilted showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro rolling showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro ardent showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro bouncy showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro crystal showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro eloquent showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro dashing showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro galactic showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro foxy showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
iron

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro lunar showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro jade showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro indigo showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro hydro showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro kinetic showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro melodic showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange

No version for distro noetic showing humble. Known supported distros are highlighted in the buttons above.

situational_graphs_reasoning package from situational_graphs_reasoning repo

situational_graphs_reasoning

ROS Distro
humble

Package Summary

Tags	No category tags.
Version	0.0.1
License	GPLv3
Build type	AMENT_PYTHON
Use	RECOMMENDED

Repository Summary

Checkout URI	https://github.com/snt-arg/situational_graphs_reasoning.git
VCS Type	git
VCS Version	develop
Last Updated	2024-08-05
Dev Status	MAINTAINED
CI status	No Continuous Integration
Released	RELEASED
Tags	No category tags.
Contributing	Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

Package Description

Graph reasoning for extracting semantic concepts using GNNs

Additional Links

No additional links.

Maintainers

adminpc

Authors

No additional authors.

Learning High-level Semantic-Relational Concepts for SLAM

Situational Graphs - Reasoning

Situational Graphs - Reasoning is a ROS2 package for generating in real-time semantic concepts like Rooms and Walls from Wall Surfaces S-Graphs. For that purpose, Graph Neural Networks (GNNs) are used to estimate the existing relations between the wall surfaces.

📜 Table of contents

📖 Published Papers

⚙️ Installation

[!NOTE] Situational Graphs - Reasoning was only tested on Ubuntu 20.04, ROS2 Foxy, Humble Distros. We strongly recommend using cyclone_dds instead of the default fastdds.

📦 Installation with S-Graphs

📦 Installation From Source

[!IMPORTANT] Before proceeding, make sure you have rosdep installed. You can install it using sudo apt-get install python3-rosdep In addition, ssh keys are needed to be configured on you GitHub account. If you haven’t yet configured ssh keys, follow this tutorial

Update Rosdep:

rosdep init && rosdep update --include-eol-distros

Create a ROS2 workspace for S-Graphs

mkdir -p $HOME/workspaces && cd $HOME/workspaces

Clone the S-Graphs repository into the created workspace

git clone git@github.com:snt-arg/situational_graphs_reasoning.git -b develop

[!IMPORTANT] If you have Nvidia GPU please install CUDA from this link. This code has only been tested with CUDA 11.8. If you dont have CUDA S-Graphs will use CPU only.

Install required dependencies. Change $ROS_DISTRO to your ros2 version.

cd situational_graphs_reasoning && source /opt/ros/$ROS_DISTRO/setup.sh && pip3 install -r requirements.txt

[!NOTE] If you want to compile with debug traces (from backward_cpp) run:

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

🚀 Usage

Follow the S-Graphs instructions to use this package along with all other functionalities.

Or launch situational_graphs_reasoning.py.

⚙️ Configuration files

File name	Description
`config/same_room_training.json`	Describes the data preprocessing and the GNN hyperparameters for room generation.
`config/same_wall_training.json`	Describes the data preprocessing and the GNN hyperparameters for wall generation.

📥 Subscribed Topics

`situational_graphs_reasoning_node` node

Topic name

Message Type

Description

File truncated at 100 lines see the full file

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.

Package Dependencies

Deps	Name
	ament_copyright
	ament_flake8
	ament_pep257
	situational_graphs_msgs
	situational_graphs_reasoning_msgs
	situational_graphs_datasets
	situational_graphs_wrapper

System Dependencies

Name
python3-pytest
python3-pytorch-pip
python3-torch-geometric-pip
python3-protobuf
python3-networkx
python3-numpy
python3-matplotlib
python3-colorama
python3-shapely
python3-seaborn
python3-transforms3d

Dependant Packages

Name	Deps
lidar_situational_graphs

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `situational_graphs_reasoning` at Robotics Stack Exchange