OK. I see you have a pendulum and a cart-pole model as examples; something like that is very easy to set up. RigidBodyDynamics can load URDFs, so you could just take the cart-pole URDF from bullet and load it as follows:

```
urdf = download("https://raw.githubusercontent.com/bulletphysics/bullet3/0e1dce41eab75fd210ec73a52adbf249710c8edf/data/cartpole.urdf", "cartpole.urdf")
using RigidBodyDynamics
cartpole = parse_urdf(Float64, urdf)
```

which results in

```
Spanning tree:
Vertex: world (root)
Vertex: slideBar, Edge: slideBar_to_world
Vertex: cart, Edge: slider_to_cart
Vertex: pole, Edge: cart_to_pole
No non-tree joints.
```

Then, to evaluate the dynamics, you can do:

```
state = MechanismState(cartpole)
fixedjoint, slidingjoint, pinjoint = joints(cartpole) # unpack joints
configuration(state, slidingjoint) .= 0.1
configuration(state, pinjoint) .= 0.2
velocity(state) .= 0
result = DynamicsResult(cartpole)
dynamics!(result, state)
```

after which the joint accelerations can be retrieved from `result`

using

```
julia> result.vĢ
2-element RigidBodyDynamics.CustomCollections.SegmentedVector{RigidBodyDynamics.JointID,Float64,Base.OneTo{RigidBodyDynamics.JointID},Array{Float64,1}}:
-3.29629
7.39932
```

And you can follow the RigidBodySim quickstart guide to simulate. If you need gradients, check out this notebook.

Note that there are some visualization changes coming soon in RigidBodySim (https://github.com/JuliaRobotics/RigidBodySim.jl/pull/64): fully switching to MeshCat.jl for visualization, making RigidBodySim quicker to install and available on Windows, among other things. Reducing load time and dropping more dependencies is also on my list.