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A GPU Accelerated Quadratic Programming Solver for Model-Predictive Control

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ReLU-QP

A GPU Accelerated Quadratic Programming Solver for Model-Predictive Control. A Python implementation can be found here.

Installation

In the Julia REPL, run the following:

using Pkg
Pkg.add(url="https://github.com/RoboticExplorationLab/ReLUQP.jl.git")

Examples

To run the examples, first set up the examples environment by running the following in a Julia REPL in the examples folder (this only needs to be done once).

using Pkg
Pkg.activate(".")
Pkg.add(url="https://github.com/RoboticExplorationLab/ReLUQP.jl.git")
Pkg.instantiate()

Each of the examples can then be run. We recommend using VSCode and stepping through the code with the REPL. The examples are:

  • atlas/atlas_balancing.jl
  • quadruped_with_arm/quadruped_pickup.jl

Citation

If you find this code useful, please consider citing our paper:

@article{bishop_relu-qp_2023,
        title = {{ReLU}-{QP}: A {GPU}-Accelerated Quadratic Programming Solver for Model-Predictive Control},
        url = {http://arxiv.org/abs/2311.18056},
        author = {Bishop, Arun L. and Zhang, John Z. and Gurumurthy, Swaminathan and Tracy, Kevin and Manchester, Zachary},
        year = {2023}
}

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