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A GUI application for planning autonomous paths in FRC

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HelixNavigator

A trajectory optimization-based path planning app for FRC.

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Compatibility

HelixNavigator is compatible with FRC swerve drive robots only. The app generates json trajectories which can be followed by the a trajectory follower in the robot code.

TrajoptLib

HelixNavigator is backed by the TrajoptLib, a C++ library for generating time-optimal trajectories.

Binary Installation

You can download the latest binaries on Releases.

Linux

Use your system's package manager to install the HelixNavigator-X.X.X-linux-x64.deb artifact.

macOS

Download the HelixNavigator-X.X.X-macOS-x64.zip artifact. Extract it and place in the /Applications directory.

Windows WSL

Since the app doesn't allow trajectory generation in windows, you should run it in WSL instead.

Install Ubuntu WSL on your Windows machine.

Next, ensure you have GUI support enabled, following this tutorial.

Open an Ubuntu WSL terminal and install HelixNavigator (this is using v1.0.1, but you can replace with any version):

wget https://github.com/TripleHelixProgramming/HelixNavigator/releases/download/v1.0.1/helixnavigator_1.0.1-1_amd64.deb
sudo dpkg -i helixnavigator_1.0.1-1_amd64.deb

After it installs, you can run /opt/helixnavigator/bin/HelixNavigator to open the app.


Windows (native, not working)

DISCLAIMER: The Windows distribution does not support generation of trajectories. This is an ongoing issue which will be fixed in the future. For now, you can run the app in WSL, see above.

Download the HelixNavigator-X.X.X-windows-x64.msi artifact and install it.

Building from source

First, clone the repo in your working directory:

git clone https://github.com/TripleHelixProgramming/HelixNavigator.git

If on Windows, replace ./gradlew with .\gradlew.bat.

To build:

./gradlew build -PmvnUsername=YOUR_USERNAME -PmvnPassword=YOUR_GITHUB_TOKEN

To run:

./gradlew run

Build packaged distribution

Run the following to build a .deb, .dmg, or .msi package:

./gradlew jpackage

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A GUI application for planning autonomous paths in FRC

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