openscvx

Pre-release

This release is a pre-release and may not be stable for production use.

Getting Started

Installation

Stable

To grab the latest stable release simply run

pip install openscvx

to install OpenSCVx in your python environment.

Or using uv:

uv pip install openscvx

For optional dependencies:

pip install openscvx[gui,cvxpygen]
# or with uv
uv pip install openscvx[gui,cvxpygen]

Nightly

To install the latest development version (nightly):

pip install --pre openscvx

With optional dependencies:

pip install --pre openscvx[gui,cvxpygen]

Or using uv:

uv pip install --pre openscvx
# With optional dependencies
uv pip install --pre openscvx[gui,cvxpygen]

Note: The --pre flag tells pip/uv to install pre-release versions (e.g., 1.2.4.dev3) from PyPI.

Alternatively, for local development with the latest source:

# Clone the repo
git clone https://github.com/OpenSCvx/OpenSCvx.git
cd OpenSCvx

# Install in editable/development mode
pip install -e .
# or with uv
uv pip install -e .

Dependencies

The main packages are:

cvxpy - is used to formulate and solve the convex subproblems
jax - is used for determining the Jacobians using automatic differentiation, vectorization, and ahead-of-time (AOT) compilation of the dynamics and their Jacobians
numpy - is used for numerical operations
diffrax - is used for the numerical integration of the dynamics
termcolor - is used for pretty command line output
plotly - is used for all visualizations

These will be installed automatically, but can be installed via conda or pip if you are building from source.

GUI Dependencies (Optional)

For interactive 3D plotting and real-time visualization, additional packages are required:

pyqtgraph - is used for interactive 3D plotting and real-time visualization
PyQt5 - provides the Qt5 GUI framework for pyqtgraph
scipy - is used for spatial transformations in plotting functions
PyOpenGL - provides OpenGL bindings for Python, required for 3D plotting
PyOpenGL_accelerate - (optional) speeds up PyOpenGL

For local development:

pip install -e ".[gui]"

CVXPYGen Dependencies (Optional)

For code generation and faster solver performance, CVXPYGen can be installed:

cvxpygen - enables code generation for faster solver performance
qocogen - custom solver backend for CVXPYGen (included with cvxpygen extras)

To install with CVXPYGen support:

pip install openscvx[cvxpygen]

Or for both GUI and CVXPYGen:

pip install openscvx[gui,cvxpygen]

CVXPYGen features include:

Automatic C++ code generation for optimization problems
Faster solver performance through compiled code
Support for custom solver backends like QOCOGen

Local Development

This git repository can be installed using https

git clone https://github.com/OpenSCvx/OpenSCvx.git

or ssh

git clone git@github.com:haynec/OpenSCvx.git

Dependencies can then be installed using Conda or Pip

Via Conda

Clone the repo using https or ssh
Create a conda environment with Python:
```
conda create -n openscvx python>=3.9
```
Activate the environment:
```
conda activate openscvx
```
Install the package with dependencies:
```
pip install -e .
```
Or install with optional dependencies:
```
pip install -e ".[gui,cvxpygen]"
```

Via uv

Prerequisites
- Install uv
Clone the repo using https or ssh

Create virtual environment and install the package:

uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install -e .

Or install with optional dependencies:

uv pip install -e ".[gui,cvxpygen]"

Via pip

Prerequisites Python >= 3.9
Clone the repo using https or ssh
Create virtual environment (called venv here) and source it
```
python3 -m venv venv
source venv/bin/activate
```
Install the package with dependencies:
```
pip install -e .
```
Or install with optional dependencies:
```
pip install -e ".[gui,cvxpygen]"
```

Running Trajectory Optimization

See examples/ folder for several example trajectory optimization problems grouped by application. To run a problem simply run any of the examples directly, for example:

python3 examples/abstract/brachistochrone.py

Note: To run the examples, you'll need to clone this repository and install OpenSCvx in editable mode (pip install -e .). See the Local Development section above for detailed installation instructions.

and adjust the plotting as needed.

Check out the problem definitions inside examples/ to see how to define your own problems.

Code Structure

ToDos

Standardized Vehicle and Constraint classes
Implement QOCOGen with CVPYGEN
Non-Dilated Time Propagation
Save and reload the compiled JAX code
Unified Mathematical Interface
Auto-SCvx Weight Tuning
Compiled at the subproblem level with JAX
Single Shot propagation

What is implemented

This repo has the following features:

Free Final Time
Fully adaptive time dilation (s is appended to the control vector)
Continuous-Time Constraint Satisfaction
FOH and ZOH exact discretization (t is a state so you can bring your own scheme)
Vectorized and Ahead-of-Time (AOT) Compiled Multishooting Discretization
JAX Autodiff for Jacobians

(back to top)

Acknowledgements

This work was supported by a NASA Space Technology Graduate Research Opportunity and the Office of Naval Research under grant N00014-17-1-2433. The authors would like to acknowledge Natalia Pavlasek, Samuel Buckner, Abhi Kamath, Govind Chari, and Purnanand Elango as well as the other Autonomous Controls Laboratory members, for their many helpful discussions and support throughout this work.

Citation

Please cite the following works if you use the repository,

@ARTICLE{hayner2025los,
        author={Hayner, Christopher R. and Carson III, John M. and Açıkmeşe, Behçet and Leung, Karen},
        journal={IEEE Robotics and Automation Letters}, 
        title={Continuous-Time Line-of-Sight Constrained Trajectory Planning for 6-Degree of Freedom Systems}, 
        year={2025},
        volume={},
        number={},
        pages={1-8},
        keywords={Robot sensing systems;Vectors;Vehicle dynamics;Line-of-sight propagation;Trajectory planning;Trajectory optimization;Quadrotors;Nonlinear dynamical systems;Heuristic algorithms;Convergence;Constrained Motion Planning;Optimization and Optimal Control;Aerial Systems: Perception and Autonomy},
        doi={10.1109/LRA.2025.3545299}}

@misc{elango2024ctscvx,
      title={Successive Convexification for Trajectory Optimization with Continuous-Time Constraint Satisfaction}, 
      author={Purnanand Elango and Dayou Luo and Abhinav G. Kamath and Samet Uzun and Taewan Kim and Behçet Açıkmeşe},
      year={2024},
      eprint={2404.16826},
      archivePrefix={arXiv},
      primaryClass={math.OC},
      url={https://arxiv.org/abs/2404.16826}, 
}

@misc{chari2025qoco,
  title = {QOCO: A Quadratic Objective Conic Optimizer with Custom Solver Generation},
  author = {Chari, Govind M and A{\c{c}}{\i}kme{\c{s}}e, Beh{\c{c}}et},
  year = {2025},
  eprint = {2503.12658},
  archiveprefix = {arXiv},
  primaryclass = {math.OC},
}

Metadata

Release files for openscvx 0.3.2.dev274

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Source distribution for openscvx 0.3.2.dev274
File	Size	Uploaded
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Built distribution (wheel)

Table of built distributions (wheels) for openscvx 0.3.2.dev274
File	Interpreter	ABI	Platform	Reset
openscvx-0.3.2.dev274-py3-none-any.whl 247.0 kB Jan 13, 2026	Python 3	none	any	Details

Total release size: 33.2 MB

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