ROS Index
|
learned_frontier_detector package from frontier_exploration repofrontier_exploration frontier_interfaces learned_frontier_detector |
ROS Distro
|
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | TODO: License declaration |
| Build type | AMENT_PYTHON |
| Use | RECOMMENDED |
Repository Summary
| Description | A frontier exploration module implementied with ROS 2, C++, and Python. |
| Checkout URI | https://github.com/adrian-soch/frontier_exploration.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2023-11-21 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | robotics pytorch ros2 frontier-exploration |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- adrian
Authors
learning based frontier detection
This is a ROS 2 package that consumes an occupancy grid map and finds frontiers. It acts as a server to any node that requests a frontier goal pose.
Setup
pip install -r requirements.txt
colcon build
Run
ros2 run learned_frontier_detector frontier_detector
Training
Roboflow was used to label the dataset. Then a google colab notebook was used to perfrom transfer learning with the custom dataset.
See yolov5-custom-training-64.ipynb for the commands to train the network. The backbone of the network was frozen to finetune the head of the network.
Resources
-
Transfer learning - The key take away is to freeze the backbone to only update the head layers during training. This is beneficial when the data set is small and you want to benefit from the pre-trained backbone. To determine which layers to freeze look at the model structure to determine the number of layers.
Package Dependencies
| Deps | Name |
|---|---|
| ament_copyright | |
| ament_flake8 | |
| ament_pep257 | |
| geometry_msgs | |
| nav_msgs | |
| action_msgs | |
| visualization_msgs | |
| tf2 | |
| tf2_ros | |
| tf2_geometry_msgs | |
| frontier_interfaces |
System Dependencies
| Name |
|---|
| python3-pytest |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged learned_frontier_detector at Robotics Stack Exchange
|
|
learned_frontier_detector package from frontier_exploration repofrontier_exploration frontier_interfaces learned_frontier_detector |
ROS Distro
|
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | TODO: License declaration |
| Build type | AMENT_PYTHON |
| Use | RECOMMENDED |
Repository Summary
| Description | A frontier exploration module implementied with ROS 2, C++, and Python. |
| Checkout URI | https://github.com/adrian-soch/frontier_exploration.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2023-11-21 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | robotics pytorch ros2 frontier-exploration |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- adrian
Authors
learning based frontier detection
This is a ROS 2 package that consumes an occupancy grid map and finds frontiers. It acts as a server to any node that requests a frontier goal pose.
Setup
pip install -r requirements.txt
colcon build
Run
ros2 run learned_frontier_detector frontier_detector
Training
Roboflow was used to label the dataset. Then a google colab notebook was used to perfrom transfer learning with the custom dataset.
See yolov5-custom-training-64.ipynb for the commands to train the network. The backbone of the network was frozen to finetune the head of the network.
Resources
-
Transfer learning - The key take away is to freeze the backbone to only update the head layers during training. This is beneficial when the data set is small and you want to benefit from the pre-trained backbone. To determine which layers to freeze look at the model structure to determine the number of layers.
Package Dependencies
| Deps | Name |
|---|---|
| ament_copyright | |
| ament_flake8 | |
| ament_pep257 | |
| geometry_msgs | |
| nav_msgs | |
| action_msgs | |
| visualization_msgs | |
| tf2 | |
| tf2_ros | |
| tf2_geometry_msgs | |
| frontier_interfaces |
System Dependencies
| Name |
|---|
| python3-pytest |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged learned_frontier_detector at Robotics Stack Exchange
|
|
learned_frontier_detector package from frontier_exploration repofrontier_exploration frontier_interfaces learned_frontier_detector |
ROS Distro
|
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | TODO: License declaration |
| Build type | AMENT_PYTHON |
| Use | RECOMMENDED |
Repository Summary
| Description | A frontier exploration module implementied with ROS 2, C++, and Python. |
| Checkout URI | https://github.com/adrian-soch/frontier_exploration.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2023-11-21 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | robotics pytorch ros2 frontier-exploration |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- adrian
Authors
learning based frontier detection
This is a ROS 2 package that consumes an occupancy grid map and finds frontiers. It acts as a server to any node that requests a frontier goal pose.
Setup
pip install -r requirements.txt
colcon build
Run
ros2 run learned_frontier_detector frontier_detector
Training
Roboflow was used to label the dataset. Then a google colab notebook was used to perfrom transfer learning with the custom dataset.
See yolov5-custom-training-64.ipynb for the commands to train the network. The backbone of the network was frozen to finetune the head of the network.
Resources
-
Transfer learning - The key take away is to freeze the backbone to only update the head layers during training. This is beneficial when the data set is small and you want to benefit from the pre-trained backbone. To determine which layers to freeze look at the model structure to determine the number of layers.
Package Dependencies
| Deps | Name |
|---|---|
| ament_copyright | |
| ament_flake8 | |
| ament_pep257 | |
| geometry_msgs | |
| nav_msgs | |
| action_msgs | |
| visualization_msgs | |
| tf2 | |
| tf2_ros | |
| tf2_geometry_msgs | |
| frontier_interfaces |
System Dependencies
| Name |
|---|
| python3-pytest |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged learned_frontier_detector at Robotics Stack Exchange
|
|
learned_frontier_detector package from frontier_exploration repofrontier_exploration frontier_interfaces learned_frontier_detector |
ROS Distro
|
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | TODO: License declaration |
| Build type | AMENT_PYTHON |
| Use | RECOMMENDED |
Repository Summary
| Description | A frontier exploration module implementied with ROS 2, C++, and Python. |
| Checkout URI | https://github.com/adrian-soch/frontier_exploration.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2023-11-21 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | robotics pytorch ros2 frontier-exploration |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- adrian
Authors
learning based frontier detection
This is a ROS 2 package that consumes an occupancy grid map and finds frontiers. It acts as a server to any node that requests a frontier goal pose.
Setup
pip install -r requirements.txt
colcon build
Run
ros2 run learned_frontier_detector frontier_detector
Training
Roboflow was used to label the dataset. Then a google colab notebook was used to perfrom transfer learning with the custom dataset.
See yolov5-custom-training-64.ipynb for the commands to train the network. The backbone of the network was frozen to finetune the head of the network.
Resources
-
Transfer learning - The key take away is to freeze the backbone to only update the head layers during training. This is beneficial when the data set is small and you want to benefit from the pre-trained backbone. To determine which layers to freeze look at the model structure to determine the number of layers.
Package Dependencies
| Deps | Name |
|---|---|
| ament_copyright | |
| ament_flake8 | |
| ament_pep257 | |
| geometry_msgs | |
| nav_msgs | |
| action_msgs | |
| visualization_msgs | |
| tf2 | |
| tf2_ros | |
| tf2_geometry_msgs | |
| frontier_interfaces |
System Dependencies
| Name |
|---|
| python3-pytest |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged learned_frontier_detector at Robotics Stack Exchange
|
|
learned_frontier_detector package from frontier_exploration repofrontier_exploration frontier_interfaces learned_frontier_detector |
ROS Distro
|
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | TODO: License declaration |
| Build type | AMENT_PYTHON |
| Use | RECOMMENDED |
Repository Summary
| Description | A frontier exploration module implementied with ROS 2, C++, and Python. |
| Checkout URI | https://github.com/adrian-soch/frontier_exploration.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2023-11-21 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | robotics pytorch ros2 frontier-exploration |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- adrian
Authors
learning based frontier detection
This is a ROS 2 package that consumes an occupancy grid map and finds frontiers. It acts as a server to any node that requests a frontier goal pose.
Setup
pip install -r requirements.txt
colcon build
Run
ros2 run learned_frontier_detector frontier_detector
Training
Roboflow was used to label the dataset. Then a google colab notebook was used to perfrom transfer learning with the custom dataset.
See yolov5-custom-training-64.ipynb for the commands to train the network. The backbone of the network was frozen to finetune the head of the network.
Resources
-
Transfer learning - The key take away is to freeze the backbone to only update the head layers during training. This is beneficial when the data set is small and you want to benefit from the pre-trained backbone. To determine which layers to freeze look at the model structure to determine the number of layers.
Package Dependencies
| Deps | Name |
|---|---|
| ament_copyright | |
| ament_flake8 | |
| ament_pep257 | |
| geometry_msgs | |
| nav_msgs | |
| action_msgs | |
| visualization_msgs | |
| tf2 | |
| tf2_ros | |
| tf2_geometry_msgs | |
| frontier_interfaces |
System Dependencies
| Name |
|---|
| python3-pytest |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged learned_frontier_detector at Robotics Stack Exchange
|
|
learned_frontier_detector package from frontier_exploration repofrontier_exploration frontier_interfaces learned_frontier_detector |
ROS Distro
|
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | TODO: License declaration |
| Build type | AMENT_PYTHON |
| Use | RECOMMENDED |
Repository Summary
| Description | A frontier exploration module implementied with ROS 2, C++, and Python. |
| Checkout URI | https://github.com/adrian-soch/frontier_exploration.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2023-11-21 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | robotics pytorch ros2 frontier-exploration |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- adrian
Authors
learning based frontier detection
This is a ROS 2 package that consumes an occupancy grid map and finds frontiers. It acts as a server to any node that requests a frontier goal pose.
Setup
pip install -r requirements.txt
colcon build
Run
ros2 run learned_frontier_detector frontier_detector
Training
Roboflow was used to label the dataset. Then a google colab notebook was used to perfrom transfer learning with the custom dataset.
See yolov5-custom-training-64.ipynb for the commands to train the network. The backbone of the network was frozen to finetune the head of the network.
Resources
-
Transfer learning - The key take away is to freeze the backbone to only update the head layers during training. This is beneficial when the data set is small and you want to benefit from the pre-trained backbone. To determine which layers to freeze look at the model structure to determine the number of layers.
Package Dependencies
| Deps | Name |
|---|---|
| ament_copyright | |
| ament_flake8 | |
| ament_pep257 | |
| geometry_msgs | |
| nav_msgs | |
| action_msgs | |
| visualization_msgs | |
| tf2 | |
| tf2_ros | |
| tf2_geometry_msgs | |
| frontier_interfaces |
System Dependencies
| Name |
|---|
| python3-pytest |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged learned_frontier_detector at Robotics Stack Exchange
|
|
learned_frontier_detector package from frontier_exploration repofrontier_exploration frontier_interfaces learned_frontier_detector |
ROS Distro
|
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | TODO: License declaration |
| Build type | AMENT_PYTHON |
| Use | RECOMMENDED |
Repository Summary
| Description | A frontier exploration module implementied with ROS 2, C++, and Python. |
| Checkout URI | https://github.com/adrian-soch/frontier_exploration.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2023-11-21 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | robotics pytorch ros2 frontier-exploration |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- adrian
Authors
learning based frontier detection
This is a ROS 2 package that consumes an occupancy grid map and finds frontiers. It acts as a server to any node that requests a frontier goal pose.
Setup
pip install -r requirements.txt
colcon build
Run
ros2 run learned_frontier_detector frontier_detector
Training
Roboflow was used to label the dataset. Then a google colab notebook was used to perfrom transfer learning with the custom dataset.
See yolov5-custom-training-64.ipynb for the commands to train the network. The backbone of the network was frozen to finetune the head of the network.
Resources
-
Transfer learning - The key take away is to freeze the backbone to only update the head layers during training. This is beneficial when the data set is small and you want to benefit from the pre-trained backbone. To determine which layers to freeze look at the model structure to determine the number of layers.
Package Dependencies
| Deps | Name |
|---|---|
| ament_copyright | |
| ament_flake8 | |
| ament_pep257 | |
| geometry_msgs | |
| nav_msgs | |
| action_msgs | |
| visualization_msgs | |
| tf2 | |
| tf2_ros | |
| tf2_geometry_msgs | |
| frontier_interfaces |
System Dependencies
| Name |
|---|
| python3-pytest |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged learned_frontier_detector at Robotics Stack Exchange
|
|
learned_frontier_detector package from frontier_exploration repofrontier_exploration frontier_interfaces learned_frontier_detector |
ROS Distro
|
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | TODO: License declaration |
| Build type | AMENT_PYTHON |
| Use | RECOMMENDED |
Repository Summary
| Description | A frontier exploration module implementied with ROS 2, C++, and Python. |
| Checkout URI | https://github.com/adrian-soch/frontier_exploration.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2023-11-21 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | robotics pytorch ros2 frontier-exploration |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- adrian
Authors
learning based frontier detection
This is a ROS 2 package that consumes an occupancy grid map and finds frontiers. It acts as a server to any node that requests a frontier goal pose.
Setup
pip install -r requirements.txt
colcon build
Run
ros2 run learned_frontier_detector frontier_detector
Training
Roboflow was used to label the dataset. Then a google colab notebook was used to perfrom transfer learning with the custom dataset.
See yolov5-custom-training-64.ipynb for the commands to train the network. The backbone of the network was frozen to finetune the head of the network.
Resources
-
Transfer learning - The key take away is to freeze the backbone to only update the head layers during training. This is beneficial when the data set is small and you want to benefit from the pre-trained backbone. To determine which layers to freeze look at the model structure to determine the number of layers.
Package Dependencies
| Deps | Name |
|---|---|
| ament_copyright | |
| ament_flake8 | |
| ament_pep257 | |
| geometry_msgs | |
| nav_msgs | |
| action_msgs | |
| visualization_msgs | |
| tf2 | |
| tf2_ros | |
| tf2_geometry_msgs | |
| frontier_interfaces |
System Dependencies
| Name |
|---|
| python3-pytest |
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged learned_frontier_detector at Robotics Stack Exchange
|
|
learned_frontier_detector package from frontier_exploration repofrontier_exploration frontier_interfaces learned_frontier_detector |
ROS Distro
|
Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | TODO: License declaration |
| Build type | AMENT_PYTHON |
| Use | RECOMMENDED |
Repository Summary
| Description | A frontier exploration module implementied with ROS 2, C++, and Python. |
| Checkout URI | https://github.com/adrian-soch/frontier_exploration.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2023-11-21 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Tags | robotics pytorch ros2 frontier-exploration |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- adrian
Authors
learning based frontier detection
This is a ROS 2 package that consumes an occupancy grid map and finds frontiers. It acts as a server to any node that requests a frontier goal pose.
Setup
pip install -r requirements.txt
colcon build
Run
ros2 run learned_frontier_detector frontier_detector
Training
Roboflow was used to label the dataset. Then a google colab notebook was used to perfrom transfer learning with the custom dataset.
See yolov5-custom-training-64.ipynb for the commands to train the network. The backbone of the network was frozen to finetune the head of the network.
Resources
-
Transfer learning - The key take away is to freeze the backbone to only update the head layers during training. This is beneficial when the data set is small and you want to benefit from the pre-trained backbone. To determine which layers to freeze look at the model structure to determine the number of layers.
Package Dependencies
| Deps | Name |
|---|---|
| ament_copyright | |
| ament_flake8 | |
| ament_pep257 | |
| geometry_msgs | |
| nav_msgs | |
| action_msgs | |
| visualization_msgs | |
| tf2 | |
| tf2_ros | |
| tf2_geometry_msgs | |
| frontier_interfaces |
System Dependencies
| Name |
|---|
| python3-pytest |