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robotic_arm_environment repository

my_doosan_pkg my_environment_pkg my_sphere_pkg

ROS Distro
github

Repository Summary

Description Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.
Checkout URI https://github.com/dvalenciar/robotic_arm_environment.git
VCS Type git
VCS Version main
Last Updated 2024-09-12
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
my_doosan_pkg 0.0.0
my_environment_pkg 0.0.0
my_sphere_pkg 0.0.0

README


Robotic Arm Simulation in ROS2 and Gazebo

Note:

I will take this project again very soon; the idea is to use state-of-the-art RL algorithms. Also, move to the new gazebo and the latest ROS version. Please let me know if you want to collaborate.

General Overview

This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZEBO and ROS2. Second, it provides a custom Reinforcement Learning Environment where you can test the Robotic Arm with your RL algorithms. Finally, we test the simulation and environment with a reacher target task, using RL and the 6DoF Robotic Arm with a visual target point.

Prerequisites

Library Version (TESTED)
Ubuntu 20.04
ROS2 Foxy link
ros2_control link
gazebo_ros2_control link

How to run this Repository

In the following links you can find a step-by-step instruction section to run this repository and simulate the robotic arm:

  • Simulation in Gazebo and ROS2 –> Tutorial-link
    • Configurate and spawn the robotic arm in Gazebo.
    • Move the robot with a simple position controller.
  • Custom RL Environment –> Tutorial-link
    • A complete Reinforcement Learning environment simulation.
  • Reacher task with RL –> Cooming soon
    • Robot reacher task.

Citation

If you use either the code, data or the step from the tutorial-blog in your paper or project, please kindly star this repo and cite our webpage

Acknowledgement

I want to thank Doosan Robotics for their repositories, and packages where they took part of this code.

  • https://github.com/doosan-robotics/doosan-robot2
  • https://github.com/doosan-robotics/doosan-robot
  • https://www.doosanrobotics.com/en/Index

Also, thanks to the authors of these repositories and their tutorials where I took some ideas

  • https://github.com/noshluk2/ROS2-Ultimate-learners-Repository/tree/main/bazu
  • https://github.com/TomasMerva/ROS_KUKA_env

Contact

Please feel free to contact me or open an issue if you have questions or need additional explanations.

The released codes are only allowed for non-commercial use.

CONTRIBUTING

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

robotic_arm_environment repository

my_doosan_pkg my_environment_pkg my_sphere_pkg

ROS Distro
github

Repository Summary

Description Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.
Checkout URI https://github.com/dvalenciar/robotic_arm_environment.git
VCS Type git
VCS Version main
Last Updated 2024-09-12
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
my_doosan_pkg 0.0.0
my_environment_pkg 0.0.0
my_sphere_pkg 0.0.0

README


Robotic Arm Simulation in ROS2 and Gazebo

Note:

I will take this project again very soon; the idea is to use state-of-the-art RL algorithms. Also, move to the new gazebo and the latest ROS version. Please let me know if you want to collaborate.

General Overview

This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZEBO and ROS2. Second, it provides a custom Reinforcement Learning Environment where you can test the Robotic Arm with your RL algorithms. Finally, we test the simulation and environment with a reacher target task, using RL and the 6DoF Robotic Arm with a visual target point.

Prerequisites

Library Version (TESTED)
Ubuntu 20.04
ROS2 Foxy link
ros2_control link
gazebo_ros2_control link

How to run this Repository

In the following links you can find a step-by-step instruction section to run this repository and simulate the robotic arm:

  • Simulation in Gazebo and ROS2 –> Tutorial-link
    • Configurate and spawn the robotic arm in Gazebo.
    • Move the robot with a simple position controller.
  • Custom RL Environment –> Tutorial-link
    • A complete Reinforcement Learning environment simulation.
  • Reacher task with RL –> Cooming soon
    • Robot reacher task.

Citation

If you use either the code, data or the step from the tutorial-blog in your paper or project, please kindly star this repo and cite our webpage

Acknowledgement

I want to thank Doosan Robotics for their repositories, and packages where they took part of this code.

  • https://github.com/doosan-robotics/doosan-robot2
  • https://github.com/doosan-robotics/doosan-robot
  • https://www.doosanrobotics.com/en/Index

Also, thanks to the authors of these repositories and their tutorials where I took some ideas

  • https://github.com/noshluk2/ROS2-Ultimate-learners-Repository/tree/main/bazu
  • https://github.com/TomasMerva/ROS_KUKA_env

Contact

Please feel free to contact me or open an issue if you have questions or need additional explanations.

The released codes are only allowed for non-commercial use.

CONTRIBUTING

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

robotic_arm_environment repository

my_doosan_pkg my_environment_pkg my_sphere_pkg

ROS Distro
github

Repository Summary

Description Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.
Checkout URI https://github.com/dvalenciar/robotic_arm_environment.git
VCS Type git
VCS Version main
Last Updated 2024-09-12
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
my_doosan_pkg 0.0.0
my_environment_pkg 0.0.0
my_sphere_pkg 0.0.0

README


Robotic Arm Simulation in ROS2 and Gazebo

Note:

I will take this project again very soon; the idea is to use state-of-the-art RL algorithms. Also, move to the new gazebo and the latest ROS version. Please let me know if you want to collaborate.

General Overview

This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZEBO and ROS2. Second, it provides a custom Reinforcement Learning Environment where you can test the Robotic Arm with your RL algorithms. Finally, we test the simulation and environment with a reacher target task, using RL and the 6DoF Robotic Arm with a visual target point.

Prerequisites

Library Version (TESTED)
Ubuntu 20.04
ROS2 Foxy link
ros2_control link
gazebo_ros2_control link

How to run this Repository

In the following links you can find a step-by-step instruction section to run this repository and simulate the robotic arm:

  • Simulation in Gazebo and ROS2 –> Tutorial-link
    • Configurate and spawn the robotic arm in Gazebo.
    • Move the robot with a simple position controller.
  • Custom RL Environment –> Tutorial-link
    • A complete Reinforcement Learning environment simulation.
  • Reacher task with RL –> Cooming soon
    • Robot reacher task.

Citation

If you use either the code, data or the step from the tutorial-blog in your paper or project, please kindly star this repo and cite our webpage

Acknowledgement

I want to thank Doosan Robotics for their repositories, and packages where they took part of this code.

  • https://github.com/doosan-robotics/doosan-robot2
  • https://github.com/doosan-robotics/doosan-robot
  • https://www.doosanrobotics.com/en/Index

Also, thanks to the authors of these repositories and their tutorials where I took some ideas

  • https://github.com/noshluk2/ROS2-Ultimate-learners-Repository/tree/main/bazu
  • https://github.com/TomasMerva/ROS_KUKA_env

Contact

Please feel free to contact me or open an issue if you have questions or need additional explanations.

The released codes are only allowed for non-commercial use.

CONTRIBUTING

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

robotic_arm_environment repository

my_doosan_pkg my_environment_pkg my_sphere_pkg

ROS Distro
github

Repository Summary

Description Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.
Checkout URI https://github.com/dvalenciar/robotic_arm_environment.git
VCS Type git
VCS Version main
Last Updated 2024-09-12
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
my_doosan_pkg 0.0.0
my_environment_pkg 0.0.0
my_sphere_pkg 0.0.0

README


Robotic Arm Simulation in ROS2 and Gazebo

Note:

I will take this project again very soon; the idea is to use state-of-the-art RL algorithms. Also, move to the new gazebo and the latest ROS version. Please let me know if you want to collaborate.

General Overview

This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZEBO and ROS2. Second, it provides a custom Reinforcement Learning Environment where you can test the Robotic Arm with your RL algorithms. Finally, we test the simulation and environment with a reacher target task, using RL and the 6DoF Robotic Arm with a visual target point.

Prerequisites

Library Version (TESTED)
Ubuntu 20.04
ROS2 Foxy link
ros2_control link
gazebo_ros2_control link

How to run this Repository

In the following links you can find a step-by-step instruction section to run this repository and simulate the robotic arm:

  • Simulation in Gazebo and ROS2 –> Tutorial-link
    • Configurate and spawn the robotic arm in Gazebo.
    • Move the robot with a simple position controller.
  • Custom RL Environment –> Tutorial-link
    • A complete Reinforcement Learning environment simulation.
  • Reacher task with RL –> Cooming soon
    • Robot reacher task.

Citation

If you use either the code, data or the step from the tutorial-blog in your paper or project, please kindly star this repo and cite our webpage

Acknowledgement

I want to thank Doosan Robotics for their repositories, and packages where they took part of this code.

  • https://github.com/doosan-robotics/doosan-robot2
  • https://github.com/doosan-robotics/doosan-robot
  • https://www.doosanrobotics.com/en/Index

Also, thanks to the authors of these repositories and their tutorials where I took some ideas

  • https://github.com/noshluk2/ROS2-Ultimate-learners-Repository/tree/main/bazu
  • https://github.com/TomasMerva/ROS_KUKA_env

Contact

Please feel free to contact me or open an issue if you have questions or need additional explanations.

The released codes are only allowed for non-commercial use.

CONTRIBUTING

Repo symbol

robotic_arm_environment repository

my_doosan_pkg my_environment_pkg my_sphere_pkg

ROS Distro
github

Repository Summary

Description Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.
Checkout URI https://github.com/dvalenciar/robotic_arm_environment.git
VCS Type git
VCS Version main
Last Updated 2024-09-12
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
my_doosan_pkg 0.0.0
my_environment_pkg 0.0.0
my_sphere_pkg 0.0.0

README


Robotic Arm Simulation in ROS2 and Gazebo

Note:

I will take this project again very soon; the idea is to use state-of-the-art RL algorithms. Also, move to the new gazebo and the latest ROS version. Please let me know if you want to collaborate.

General Overview

This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZEBO and ROS2. Second, it provides a custom Reinforcement Learning Environment where you can test the Robotic Arm with your RL algorithms. Finally, we test the simulation and environment with a reacher target task, using RL and the 6DoF Robotic Arm with a visual target point.

Prerequisites

Library Version (TESTED)
Ubuntu 20.04
ROS2 Foxy link
ros2_control link
gazebo_ros2_control link

How to run this Repository

In the following links you can find a step-by-step instruction section to run this repository and simulate the robotic arm:

  • Simulation in Gazebo and ROS2 –> Tutorial-link
    • Configurate and spawn the robotic arm in Gazebo.
    • Move the robot with a simple position controller.
  • Custom RL Environment –> Tutorial-link
    • A complete Reinforcement Learning environment simulation.
  • Reacher task with RL –> Cooming soon
    • Robot reacher task.

Citation

If you use either the code, data or the step from the tutorial-blog in your paper or project, please kindly star this repo and cite our webpage

Acknowledgement

I want to thank Doosan Robotics for their repositories, and packages where they took part of this code.

  • https://github.com/doosan-robotics/doosan-robot2
  • https://github.com/doosan-robotics/doosan-robot
  • https://www.doosanrobotics.com/en/Index

Also, thanks to the authors of these repositories and their tutorials where I took some ideas

  • https://github.com/noshluk2/ROS2-Ultimate-learners-Repository/tree/main/bazu
  • https://github.com/TomasMerva/ROS_KUKA_env

Contact

Please feel free to contact me or open an issue if you have questions or need additional explanations.

The released codes are only allowed for non-commercial use.

CONTRIBUTING

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

robotic_arm_environment repository

my_doosan_pkg my_environment_pkg my_sphere_pkg

ROS Distro
github

Repository Summary

Description Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.
Checkout URI https://github.com/dvalenciar/robotic_arm_environment.git
VCS Type git
VCS Version main
Last Updated 2024-09-12
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
my_doosan_pkg 0.0.0
my_environment_pkg 0.0.0
my_sphere_pkg 0.0.0

README


Robotic Arm Simulation in ROS2 and Gazebo

Note:

I will take this project again very soon; the idea is to use state-of-the-art RL algorithms. Also, move to the new gazebo and the latest ROS version. Please let me know if you want to collaborate.

General Overview

This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZEBO and ROS2. Second, it provides a custom Reinforcement Learning Environment where you can test the Robotic Arm with your RL algorithms. Finally, we test the simulation and environment with a reacher target task, using RL and the 6DoF Robotic Arm with a visual target point.

Prerequisites

Library Version (TESTED)
Ubuntu 20.04
ROS2 Foxy link
ros2_control link
gazebo_ros2_control link

How to run this Repository

In the following links you can find a step-by-step instruction section to run this repository and simulate the robotic arm:

  • Simulation in Gazebo and ROS2 –> Tutorial-link
    • Configurate and spawn the robotic arm in Gazebo.
    • Move the robot with a simple position controller.
  • Custom RL Environment –> Tutorial-link
    • A complete Reinforcement Learning environment simulation.
  • Reacher task with RL –> Cooming soon
    • Robot reacher task.

Citation

If you use either the code, data or the step from the tutorial-blog in your paper or project, please kindly star this repo and cite our webpage

Acknowledgement

I want to thank Doosan Robotics for their repositories, and packages where they took part of this code.

  • https://github.com/doosan-robotics/doosan-robot2
  • https://github.com/doosan-robotics/doosan-robot
  • https://www.doosanrobotics.com/en/Index

Also, thanks to the authors of these repositories and their tutorials where I took some ideas

  • https://github.com/noshluk2/ROS2-Ultimate-learners-Repository/tree/main/bazu
  • https://github.com/TomasMerva/ROS_KUKA_env

Contact

Please feel free to contact me or open an issue if you have questions or need additional explanations.

The released codes are only allowed for non-commercial use.

CONTRIBUTING

No version for distro iron showing github. Known supported distros are highlighted in the buttons above.
Repo symbol

robotic_arm_environment repository

my_doosan_pkg my_environment_pkg my_sphere_pkg

ROS Distro
github

Repository Summary

Description Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.
Checkout URI https://github.com/dvalenciar/robotic_arm_environment.git
VCS Type git
VCS Version main
Last Updated 2024-09-12
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
my_doosan_pkg 0.0.0
my_environment_pkg 0.0.0
my_sphere_pkg 0.0.0

README


Robotic Arm Simulation in ROS2 and Gazebo

Note:

I will take this project again very soon; the idea is to use state-of-the-art RL algorithms. Also, move to the new gazebo and the latest ROS version. Please let me know if you want to collaborate.

General Overview

This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZEBO and ROS2. Second, it provides a custom Reinforcement Learning Environment where you can test the Robotic Arm with your RL algorithms. Finally, we test the simulation and environment with a reacher target task, using RL and the 6DoF Robotic Arm with a visual target point.

Prerequisites

Library Version (TESTED)
Ubuntu 20.04
ROS2 Foxy link
ros2_control link
gazebo_ros2_control link

How to run this Repository

In the following links you can find a step-by-step instruction section to run this repository and simulate the robotic arm:

  • Simulation in Gazebo and ROS2 –> Tutorial-link
    • Configurate and spawn the robotic arm in Gazebo.
    • Move the robot with a simple position controller.
  • Custom RL Environment –> Tutorial-link
    • A complete Reinforcement Learning environment simulation.
  • Reacher task with RL –> Cooming soon
    • Robot reacher task.

Citation

If you use either the code, data or the step from the tutorial-blog in your paper or project, please kindly star this repo and cite our webpage

Acknowledgement

I want to thank Doosan Robotics for their repositories, and packages where they took part of this code.

  • https://github.com/doosan-robotics/doosan-robot2
  • https://github.com/doosan-robotics/doosan-robot
  • https://www.doosanrobotics.com/en/Index

Also, thanks to the authors of these repositories and their tutorials where I took some ideas

  • https://github.com/noshluk2/ROS2-Ultimate-learners-Repository/tree/main/bazu
  • https://github.com/TomasMerva/ROS_KUKA_env

Contact

Please feel free to contact me or open an issue if you have questions or need additional explanations.

The released codes are only allowed for non-commercial use.

CONTRIBUTING

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

robotic_arm_environment repository

my_doosan_pkg my_environment_pkg my_sphere_pkg

ROS Distro
github

Repository Summary

Description Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.
Checkout URI https://github.com/dvalenciar/robotic_arm_environment.git
VCS Type git
VCS Version main
Last Updated 2024-09-12
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
my_doosan_pkg 0.0.0
my_environment_pkg 0.0.0
my_sphere_pkg 0.0.0

README


Robotic Arm Simulation in ROS2 and Gazebo

Note:

I will take this project again very soon; the idea is to use state-of-the-art RL algorithms. Also, move to the new gazebo and the latest ROS version. Please let me know if you want to collaborate.

General Overview

This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZEBO and ROS2. Second, it provides a custom Reinforcement Learning Environment where you can test the Robotic Arm with your RL algorithms. Finally, we test the simulation and environment with a reacher target task, using RL and the 6DoF Robotic Arm with a visual target point.

Prerequisites

Library Version (TESTED)
Ubuntu 20.04
ROS2 Foxy link
ros2_control link
gazebo_ros2_control link

How to run this Repository

In the following links you can find a step-by-step instruction section to run this repository and simulate the robotic arm:

  • Simulation in Gazebo and ROS2 –> Tutorial-link
    • Configurate and spawn the robotic arm in Gazebo.
    • Move the robot with a simple position controller.
  • Custom RL Environment –> Tutorial-link
    • A complete Reinforcement Learning environment simulation.
  • Reacher task with RL –> Cooming soon
    • Robot reacher task.

Citation

If you use either the code, data or the step from the tutorial-blog in your paper or project, please kindly star this repo and cite our webpage

Acknowledgement

I want to thank Doosan Robotics for their repositories, and packages where they took part of this code.

  • https://github.com/doosan-robotics/doosan-robot2
  • https://github.com/doosan-robotics/doosan-robot
  • https://www.doosanrobotics.com/en/Index

Also, thanks to the authors of these repositories and their tutorials where I took some ideas

  • https://github.com/noshluk2/ROS2-Ultimate-learners-Repository/tree/main/bazu
  • https://github.com/TomasMerva/ROS_KUKA_env

Contact

Please feel free to contact me or open an issue if you have questions or need additional explanations.

The released codes are only allowed for non-commercial use.

CONTRIBUTING

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

robotic_arm_environment repository

my_doosan_pkg my_environment_pkg my_sphere_pkg

ROS Distro
github

Repository Summary

Description Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.
Checkout URI https://github.com/dvalenciar/robotic_arm_environment.git
VCS Type git
VCS Version main
Last Updated 2024-09-12
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Packages

Name Version
my_doosan_pkg 0.0.0
my_environment_pkg 0.0.0
my_sphere_pkg 0.0.0

README


Robotic Arm Simulation in ROS2 and Gazebo

Note:

I will take this project again very soon; the idea is to use state-of-the-art RL algorithms. Also, move to the new gazebo and the latest ROS version. Please let me know if you want to collaborate.

General Overview

This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZEBO and ROS2. Second, it provides a custom Reinforcement Learning Environment where you can test the Robotic Arm with your RL algorithms. Finally, we test the simulation and environment with a reacher target task, using RL and the 6DoF Robotic Arm with a visual target point.

Prerequisites

Library Version (TESTED)
Ubuntu 20.04
ROS2 Foxy link
ros2_control link
gazebo_ros2_control link

How to run this Repository

In the following links you can find a step-by-step instruction section to run this repository and simulate the robotic arm:

  • Simulation in Gazebo and ROS2 –> Tutorial-link
    • Configurate and spawn the robotic arm in Gazebo.
    • Move the robot with a simple position controller.
  • Custom RL Environment –> Tutorial-link
    • A complete Reinforcement Learning environment simulation.
  • Reacher task with RL –> Cooming soon
    • Robot reacher task.

Citation

If you use either the code, data or the step from the tutorial-blog in your paper or project, please kindly star this repo and cite our webpage

Acknowledgement

I want to thank Doosan Robotics for their repositories, and packages where they took part of this code.

  • https://github.com/doosan-robotics/doosan-robot2
  • https://github.com/doosan-robotics/doosan-robot
  • https://www.doosanrobotics.com/en/Index

Also, thanks to the authors of these repositories and their tutorials where I took some ideas

  • https://github.com/noshluk2/ROS2-Ultimate-learners-Repository/tree/main/bazu
  • https://github.com/TomasMerva/ROS_KUKA_env

Contact

Please feel free to contact me or open an issue if you have questions or need additional explanations.

The released codes are only allowed for non-commercial use.

CONTRIBUTING