ROS Index
Repository Summary
| Description | A fast particle filter implementation and sensor models for localization which always take into account the most recent state of the world. |
| Checkout URI | https://github.com/tue-robotics/ed_localization.git |
| VCS Type | git |
| VCS Version | master |
| Last Updated | 2025-04-18 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Packages
| Name | Version |
|---|---|
| ed_localization | 0.0.0 |
README
ED Localization
A fast particle filter implementation and sensor models for localizing a robot which always take into account the most recent state of the world. This means that if the world representation improves while the robot is running, localization becomes better. The localization module is more efficient and accurate than the well-known AMCL-module and no separate occupancy grid is needed.
Installation
Requirements:
- ED (https://github.com/tue-robotics/ed.git)
- A 2D Range Finder (http://wiki.ros.org/Sensors) which scans in a plane parallel to the floor
- A TF containing transforms from the robots’ odometry frame to the laser range finder frame
Check out the following packages in your workspace:
cd <your_catkin_workspace>/src
git clone https://github.com/tue-robotics/ed_localization.git
And compile
cd <your_catkin_workspace>:
catkin build
Tutorial
All ED tutorials can be found in the ed_tutorials package: https://github.com/tue-robotics/ed_tutorials.git
CONTRIBUTING
Repository Summary
| Description | A fast particle filter implementation and sensor models for localization which always take into account the most recent state of the world. |
| Checkout URI | https://github.com/tue-robotics/ed_localization.git |
| VCS Type | git |
| VCS Version | master |
| Last Updated | 2025-04-18 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Packages
| Name | Version |
|---|---|
| ed_localization | 0.0.0 |
README
ED Localization
A fast particle filter implementation and sensor models for localizing a robot which always take into account the most recent state of the world. This means that if the world representation improves while the robot is running, localization becomes better. The localization module is more efficient and accurate than the well-known AMCL-module and no separate occupancy grid is needed.
Installation
Requirements:
- ED (https://github.com/tue-robotics/ed.git)
- A 2D Range Finder (http://wiki.ros.org/Sensors) which scans in a plane parallel to the floor
- A TF containing transforms from the robots’ odometry frame to the laser range finder frame
Check out the following packages in your workspace:
cd <your_catkin_workspace>/src
git clone https://github.com/tue-robotics/ed_localization.git
And compile
cd <your_catkin_workspace>:
catkin build
Tutorial
All ED tutorials can be found in the ed_tutorials package: https://github.com/tue-robotics/ed_tutorials.git
CONTRIBUTING
Repository Summary
| Description | A fast particle filter implementation and sensor models for localization which always take into account the most recent state of the world. |
| Checkout URI | https://github.com/tue-robotics/ed_localization.git |
| VCS Type | git |
| VCS Version | master |
| Last Updated | 2025-04-18 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Packages
| Name | Version |
|---|---|
| ed_localization | 0.0.0 |
README
ED Localization
A fast particle filter implementation and sensor models for localizing a robot which always take into account the most recent state of the world. This means that if the world representation improves while the robot is running, localization becomes better. The localization module is more efficient and accurate than the well-known AMCL-module and no separate occupancy grid is needed.
Installation
Requirements:
- ED (https://github.com/tue-robotics/ed.git)
- A 2D Range Finder (http://wiki.ros.org/Sensors) which scans in a plane parallel to the floor
- A TF containing transforms from the robots’ odometry frame to the laser range finder frame
Check out the following packages in your workspace:
cd <your_catkin_workspace>/src
git clone https://github.com/tue-robotics/ed_localization.git
And compile
cd <your_catkin_workspace>:
catkin build
Tutorial
All ED tutorials can be found in the ed_tutorials package: https://github.com/tue-robotics/ed_tutorials.git
CONTRIBUTING
Repository Summary
| Description | A fast particle filter implementation and sensor models for localization which always take into account the most recent state of the world. |
| Checkout URI | https://github.com/tue-robotics/ed_localization.git |
| VCS Type | git |
| VCS Version | master |
| Last Updated | 2025-04-18 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Packages
| Name | Version |
|---|---|
| ed_localization | 0.0.0 |
README
ED Localization
A fast particle filter implementation and sensor models for localizing a robot which always take into account the most recent state of the world. This means that if the world representation improves while the robot is running, localization becomes better. The localization module is more efficient and accurate than the well-known AMCL-module and no separate occupancy grid is needed.
Installation
Requirements:
- ED (https://github.com/tue-robotics/ed.git)
- A 2D Range Finder (http://wiki.ros.org/Sensors) which scans in a plane parallel to the floor
- A TF containing transforms from the robots’ odometry frame to the laser range finder frame
Check out the following packages in your workspace:
cd <your_catkin_workspace>/src
git clone https://github.com/tue-robotics/ed_localization.git
And compile
cd <your_catkin_workspace>:
catkin build
Tutorial
All ED tutorials can be found in the ed_tutorials package: https://github.com/tue-robotics/ed_tutorials.git
CONTRIBUTING
Repository Summary
| Description | A fast particle filter implementation and sensor models for localization which always take into account the most recent state of the world. |
| Checkout URI | https://github.com/tue-robotics/ed_localization.git |
| VCS Type | git |
| VCS Version | master |
| Last Updated | 2025-04-18 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Packages
| Name | Version |
|---|---|
| ed_localization | 0.0.0 |
README
ED Localization
A fast particle filter implementation and sensor models for localizing a robot which always take into account the most recent state of the world. This means that if the world representation improves while the robot is running, localization becomes better. The localization module is more efficient and accurate than the well-known AMCL-module and no separate occupancy grid is needed.
Installation
Requirements:
- ED (https://github.com/tue-robotics/ed.git)
- A 2D Range Finder (http://wiki.ros.org/Sensors) which scans in a plane parallel to the floor
- A TF containing transforms from the robots’ odometry frame to the laser range finder frame
Check out the following packages in your workspace:
cd <your_catkin_workspace>/src
git clone https://github.com/tue-robotics/ed_localization.git
And compile
cd <your_catkin_workspace>:
catkin build
Tutorial
All ED tutorials can be found in the ed_tutorials package: https://github.com/tue-robotics/ed_tutorials.git
CONTRIBUTING
Repository Summary
| Description | A fast particle filter implementation and sensor models for localization which always take into account the most recent state of the world. |
| Checkout URI | https://github.com/tue-robotics/ed_localization.git |
| VCS Type | git |
| VCS Version | master |
| Last Updated | 2025-04-18 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Packages
| Name | Version |
|---|---|
| ed_localization | 0.0.0 |
README
ED Localization
A fast particle filter implementation and sensor models for localizing a robot which always take into account the most recent state of the world. This means that if the world representation improves while the robot is running, localization becomes better. The localization module is more efficient and accurate than the well-known AMCL-module and no separate occupancy grid is needed.
Installation
Requirements:
- ED (https://github.com/tue-robotics/ed.git)
- A 2D Range Finder (http://wiki.ros.org/Sensors) which scans in a plane parallel to the floor
- A TF containing transforms from the robots’ odometry frame to the laser range finder frame
Check out the following packages in your workspace:
cd <your_catkin_workspace>/src
git clone https://github.com/tue-robotics/ed_localization.git
And compile
cd <your_catkin_workspace>:
catkin build
Tutorial
All ED tutorials can be found in the ed_tutorials package: https://github.com/tue-robotics/ed_tutorials.git
CONTRIBUTING
Repository Summary
| Description | A fast particle filter implementation and sensor models for localization which always take into account the most recent state of the world. |
| Checkout URI | https://github.com/tue-robotics/ed_localization.git |
| VCS Type | git |
| VCS Version | master |
| Last Updated | 2025-04-18 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Packages
| Name | Version |
|---|---|
| ed_localization | 0.0.0 |
README
ED Localization
A fast particle filter implementation and sensor models for localizing a robot which always take into account the most recent state of the world. This means that if the world representation improves while the robot is running, localization becomes better. The localization module is more efficient and accurate than the well-known AMCL-module and no separate occupancy grid is needed.
Installation
Requirements:
- ED (https://github.com/tue-robotics/ed.git)
- A 2D Range Finder (http://wiki.ros.org/Sensors) which scans in a plane parallel to the floor
- A TF containing transforms from the robots’ odometry frame to the laser range finder frame
Check out the following packages in your workspace:
cd <your_catkin_workspace>/src
git clone https://github.com/tue-robotics/ed_localization.git
And compile
cd <your_catkin_workspace>:
catkin build
Tutorial
All ED tutorials can be found in the ed_tutorials package: https://github.com/tue-robotics/ed_tutorials.git
CONTRIBUTING
Repository Summary
| Description | A fast particle filter implementation and sensor models for localization which always take into account the most recent state of the world. |
| Checkout URI | https://github.com/tue-robotics/ed_localization.git |
| VCS Type | git |
| VCS Version | master |
| Last Updated | 2025-04-18 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Packages
| Name | Version |
|---|---|
| ed_localization | 0.0.0 |
README
ED Localization
A fast particle filter implementation and sensor models for localizing a robot which always take into account the most recent state of the world. This means that if the world representation improves while the robot is running, localization becomes better. The localization module is more efficient and accurate than the well-known AMCL-module and no separate occupancy grid is needed.
Installation
Requirements:
- ED (https://github.com/tue-robotics/ed.git)
- A 2D Range Finder (http://wiki.ros.org/Sensors) which scans in a plane parallel to the floor
- A TF containing transforms from the robots’ odometry frame to the laser range finder frame
Check out the following packages in your workspace:
cd <your_catkin_workspace>/src
git clone https://github.com/tue-robotics/ed_localization.git
And compile
cd <your_catkin_workspace>:
catkin build
Tutorial
All ED tutorials can be found in the ed_tutorials package: https://github.com/tue-robotics/ed_tutorials.git
CONTRIBUTING
Repository Summary
| Description | A fast particle filter implementation and sensor models for localization which always take into account the most recent state of the world. |
| Checkout URI | https://github.com/tue-robotics/ed_localization.git |
| VCS Type | git |
| VCS Version | master |
| Last Updated | 2025-04-18 |
| Dev Status | UNKNOWN |
| Released | UNRELEASED |
| Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Packages
| Name | Version |
|---|---|
| ed_localization | 0.0.0 |
README
ED Localization
A fast particle filter implementation and sensor models for localizing a robot which always take into account the most recent state of the world. This means that if the world representation improves while the robot is running, localization becomes better. The localization module is more efficient and accurate than the well-known AMCL-module and no separate occupancy grid is needed.
Installation
Requirements:
- ED (https://github.com/tue-robotics/ed.git)
- A 2D Range Finder (http://wiki.ros.org/Sensors) which scans in a plane parallel to the floor
- A TF containing transforms from the robots’ odometry frame to the laser range finder frame
Check out the following packages in your workspace:
cd <your_catkin_workspace>/src
git clone https://github.com/tue-robotics/ed_localization.git
And compile
cd <your_catkin_workspace>:
catkin build
Tutorial
All ED tutorials can be found in the ed_tutorials package: https://github.com/tue-robotics/ed_tutorials.git