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Robot Planning and Control (rpc) is a software framework designed for generating task trajectories (planning) and tracking the trajectories (control) for legged systems.

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Robot Planning and Control (rpc)

rpc is a software framework designed for generating task trajectories (planning) and tracking the trajectories (control) for legged systems.

Software Framework is developed by Seung Hyeon Bang based on the PnC Repository.

Dependencies

The controller has been tested on Ubuntu 18.04 and Mac OSX Ventura. It builds on the shoulders of the following software:

  • anaconda: For Pybullet simulator
  • python dependencies:
$ conda env create -f rpc.yml
optional dependencies
  • MatLogger2: logging numeric data (cpp to MAT-files)
  • zmq: logging numeric data
  • protobuf: logging numeric data

Usage

  • source conda environment:
$ conda activate rpc
  • Compile:
$ mkdir build
$ cd build 
$ cmake ..
$ make -j4
  • Run simulation:
python simulator/pybullet/draco_main.py
optional
  • visualization:
$ conda env create -f visualize.yml
$ conda activate visualize
$ python plot/draco/draco_data_manager.py --b_visualize=true
Hardware Usage
  • Please refer to this repository using rpc library

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Robot Planning and Control (rpc) is a software framework designed for generating task trajectories (planning) and tracking the trajectories (control) for legged systems.

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