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Real-Time Deformable-Contact-Aware Model Predictive Control for Force-Modulated Manipulation

This code is primarily uses DDP as the optimizer with autodiff for real-time implementation. The analytical model is derived using RobCoGen. control-toolbox is used to use Autodiff functionality for real-time implentation.
This repo uses DDP (Differential Dynamic Programming) + Soft-Contact inside a ADMM (Alternating Direction Multiplier Method) outer loop.

Structure

  • Standalone DDP code (C++) with a soft contact model
  • ADMM integration with constraints and DDP
  • Model Predictive Control (MPC)

Dependencies

Dynamics of the robot are computed using

Installation

mkdir build & cd build
ccmake ..

To use the eigen library installed in the system, enable the the option USE_SYSTEM_EIGEN. To build from source.

make

How to use

  • Scripts for executables can be found in src

  • Files specific to ADMM - admm

  • Files specific to DDP - ddp

  • Following executables are generated

    • admm-contact (admm with orocos KDL dynamics, finite difference)
    • admm-contact-rcg (admm with RobCoGen dynamics, AutoDiff)
    • admm-mpc-contact - (MPC - admm with orocos KDL dynamics, finite difference)
    • admm-mpc-contact-rcg - (MPC - admm with RobCoGen dynamics, AutoDiff)

Aknowledgement and Contact

Lasitha Wijayarathne - [email protected]

Ziyi Zhou - [email protected]

Citation

@article{wijayarathne2023real,
  title={Real-Time Deformable-Contact-Aware Model Predictive Control for Force-Modulated Manipulation},
  author={Wijayarathne, Lasitha and Zhou, Ziyi and Zhao, Ye and Hammond, Frank L},
  journal={IEEE Transactions on Robotics},
  year={2023},
  publisher={IEEE}
}

admm's People

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