allwpilib VS Pathfinder2

You need to be more specific, what issues? I would recommend starting with an example. https://github.com/wpilibsuite/allwpilib/tree/main/wpilibjExamples/src/main/java/edu/wpi/first/wpilibj/examples/mecanumdrive. And looking at the documentation for it here. https://docs.wpilib.org/en/stable/docs/software/hardware-apis/motors/wpi-drive-classes.html#mecanum-drive If this doesn’t work make sure your wheels are in the correct orientation (x pattern when viewed from top) and you set your inverts right.)

I believe this page has timed based swerve code https://github.com/wpilibsuite/allwpilib/tree/main/wpilibjExamples/src/main/java/edu/wpi/first/wpilibj/examples/swervebot

Study Java syntax, and look up the common code libraries at https://wpilib.org/

Just to cover all the bases, have you run the 2022 installer? That should have all of the files required to build robot projects. Even if you have I would recommend running it again and making sure that it installs the JDK to the default location.

Also remember that wpilib is open source, so you can check out the implantation of all of these classes yourself to better understand what they’re doing. Java SequentialCommandGroup is right here. You can also access this by control+left clicking on almost any class or method in vscode and it’ll open up a new editor tab with that code.

To get myself started I used Manning Robotics tutorial. Keep in mind though it is out of date as there was a rewrite for the command based framework in 2020. Check out the WPILIB for a walk through of the system. Also linked from WPILIB are the example projects gears bot and traditional hatchbot that my team has been referencing to get us started.

It's been updated, and installing it worked for me. Get the dmg from here, then download and install.

This is the link to the GitHub release https://github.com/wpilibsuite/allwpilib/releases/tag/v2019.4.1

if you’re sure you want to go the in-wheel encoder route, check out wpilib’s implementation of it here. it uses EJML for most of the math, but you can remove it if you’re comfortable with matrixes

i proudly proclaim this “the pathfinder shuffle”

i don’t hate roadrunner, but i do have an alternative - pathfinder2, a library i’ve been working on for about a year now that’s pretty similar in functionality. my team decided we weren’t going to use roadrunner because we wanted to improve the accuracy of positional tracking over time and wanted to have more control over how we could control our movement. roadrunner isn’t a bad thing - it still works pretty well and i’ve seen a lot of teams make use of it - roadrunner doesn’t appear to be in as active of development as it was before and i personally wanted a solution that was easier to use and more robust, but using roadrunner won’t mean you can’t perform well

i feel you on that. i've spent nearly a year working on a library for odometry-based autonomous navigation - our robot was capable of navigating around a field entirely autonomously - and it's quite disappointing that all of that work has no use in my last year in the FTC program. i know the change is for the better, but i feel like i've wasted a lot of time and energy

hey, i just figured i’d put this out here in case it helps: meccanum wheels, by nature, have a LOT of slip - that’s how they’re able to move in any direction. i’ve had quite a bit of experience with the math and kinematic behind this (two libraries i’ve written/am writing, Pathfinder and Pathfinder2, as well as a library the other programmer on my team wrote, OdometryCore) and it’s VERY HARD to accurately track the position of a meccanum robot only using the encoders in the wheels. it’s not impossible, but it’s very, very challenging. the more your robot moves, the less accurate it becomes, and it will very quickly report positions that are nowhere near where your robot actually is. you can go for it, but i would strongly encourage you check out three wheel odometry instead - it’s been very accurate and allowed us to do really cool things, like accurately record a robot’s movement and play it back perfectly. you’ll have much more success with three wheel odometry - my team designed a custom odometry system and i’m sure they’d be happy to give you more information if you’d like. best of luck :)