Robot-2020
The source code for the 2020 FRC robot. (by frc3512)
autodiff
automatic differentiation made easier for C++ (by autodiff)
| Robot-2020 | autodiff | |
|---|---|---|
| 1 | 7 | |
| 8 | 1,536 | |
| - | 1.2% | |
| 0.0 | 7.8 | |
| about 2 years ago | about 1 month ago | |
| C++ | C++ | |
| BSD 3-clause "New" or "Revised" License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Robot-2020
Posts with mentions or reviews of Robot-2020.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-09-27.
autodiff
Posts with mentions or reviews of autodiff.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-03-22.
- The Elements of Differentiable Programming
-
Astray: A performance-portable geodesic ray tracing library.
I completely agree. Specifying the metric rather than the Christoffel symbols would make it much easier for the users. Something like https://github.com/autodiff/autodiff might just work as the metric tensor is made up of primitives.
-
Point-to-Point Distance Constraint: Gradient of Forward Kinematics
Old username :D So far I have been using Eigen for linear algebra and NLOPT for optimization algorithms. I have found "autodiff" that hopefully looks easy to use: https://github.com/autodiff/autodiff
- Autodiff: Simple C++17 library for Automatic Differentiation
-
Gradients Without Backpropagation
Forward-mode differentiation is easy to implement in C++ with templates, operator overloading, and dual numbers (https://en.wikipedia.org/wiki/Automatic_differentiation#Auto...). Some libraries such as autodiff (https://github.com/autodiff/autodiff) and CppAD (https://github.com/coin-or/CppAD) use this method.
- Ensmallen: A C++ Library for Efficient Numerical Optimization
-
I am creating a fast, header-only, C++ library for control algorithms
I was thinking of adding [autodiff](https://github.com/autodiff/autodiff) in the future, mainly because it works seamlessly with *Eigen*. One big advantage would be that I could use it for AD for NonlinearSystems as well.
What are some alternatives?
When comparing Robot-2020 and autodiff you can also consider the following projects:
PythonRobotics - Python sample codes for robotics algorithms.
CppAD - A C++ Algorithmic Differentiation Package: Home Page
CppRobotics - Header-only C++ library for robotics, control, and path planning algorithms. Work in progress, contributions are welcome!
FastAD - FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
MathNet - Math.NET Numerics
MKL.NET - A simple cross platform .NET API for Intel MKL
Microsoft Automatic Graph Layout - A set of tools for graph layout and viewing
allwpilib - Official Repository of WPILibJ and WPILibC
geodesic_raytracing
Rationals - 🔟 Implementation of rational number arithmetic for .NET with arbitrary precision.
Robot-2020 vs PythonRobotics
autodiff vs CppAD
Robot-2020 vs CppRobotics
autodiff vs FastAD
autodiff vs MathNet
autodiff vs MKL.NET
autodiff vs CppRobotics
autodiff vs PythonRobotics
autodiff vs Microsoft Automatic Graph Layout
autodiff vs allwpilib
autodiff vs geodesic_raytracing
autodiff vs Rationals