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Merge pull request #561 from JuliaRobotics/tk/fix-notebook-link
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Fix #560, example notebooks link broken.
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tkoolen authored Jun 23, 2019
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RigidBodyDynamics.jl is a rigid body dynamics library in pure Julia. It aims to be **user friendly** and [**performant**](https://github.com/JuliaRobotics/RigidBodyDynamics.jl/blob/master/docs/src/benchmarks.md), but also **generic** in the sense that the algorithms can be called with inputs of any (suitable) scalar types. This means that if fast numeric dynamics evaluations are required, a user can supply `Float64` or `Float32` inputs. However, if symbolic quantities are desired for analysis purposes, they can be obtained by calling the algorithms with e.g. [`SymPy.Sym`](https://github.com/JuliaPy/SymPy.jl) inputs. If gradients are required, e.g. the [`ForwardDiff.Dual`](https://github.com/JuliaDiff/ForwardDiff.jl) type, which implements forward-mode [automatic differentiation](https://en.wikipedia.org/wiki/Automatic_differentiation), can be used.

See the [latest stable documentation](https://JuliaRobotics.github.io/RigidBodyDynamics.jl/stable/) for a list of features, installation instructions, and a quick-start guide. Installation should only take a couple of minutes, including installing Julia itself. See the [notebooks directory](https://github.com/JuliaRobotics/RigidBodyDynamics.jl/tree/master/notebooks) for some usage examples.
See the [latest documentation](https://JuliaRobotics.github.io/RigidBodyDynamics.jl/dev) for a list of features, installation instructions, and a quick-start guide. Installation should only take a couple of minutes, including installing Julia itself. The documentation includes various usage examples, starting with a [quickstart guide](http://www.juliarobotics.org/RigidBodyDynamics.jl/dev/generated/1.%20Quickstart%20-%20double%20pendulum/1.%20Quickstart%20-%20double%20pendulum/). These examples are also runnable locally as Jupyter notebooks; see [the readme in the examples directory](https://github.com/JuliaRobotics/RigidBodyDynamics.jl/blob/master/examples/README.md) for instructions.


## Related packages
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