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robopal: A Simulation Framework Based Mujoco

Project description

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robopal is an open source robot simulation framework based on MuJoCo, mainly used for deep reinforcement learning training and Control algorithm verification. A variety of control schemes and example environments are provided within the framework.

Compared with other frameworks, ours has the following advantages:

  • Higher motion accuracy, it is more in line with the motion in the real environment
  • High portability, more concise code, easy to learn and use
  • Rich task environment, such as compliant control, motion imitation, visual servoing, etc.

Installation

Required environments

Install from source

$ git clone https://github.com/NoneJou072/robopal
$ cd robopal
$ pip install -e .

Controller

The development version mainly includes the following controllers:

  • Joint Space Controller
    Use Ruckig to plan joint positions, velocities, accelerations for smooth motion, and calculate torques based on pd control and dynamics
  • Cartesian Space Controller
    Position/rotation control in Cartesian space based on pd control and kinematics

Project details


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robopal-0.1.1.tar.gz (22.9 kB view hashes)

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