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Author here.<p>I've spent the last six months replicating the paper "Champion-level drone racing using deep reinforcement learning" and now I'm writing down the blog posts I wish I had along the way.<p>Any feedback is welcome, especially as I'm a bit unsure if I struck the right balance between being concise and not requiring too many prerequisites.<p>Also if you're working on RL and robotics (especially aerial), let's connect!
I assume you are going to start introducing all the 2nd and 3rd order effects? One big one is ground effect, and another is vortex ring state/settling with power and the related translational lift, and the props themselves have p-factor and the dirty air effect for the rear props.
Isn't it just bi-copter?
No, it's a quadcopter setup, but simulated in a 2D world (I guess for simplicity). A bi-copter would require tiltrotors, which is different.
Physics simulations from scratch are great learning projects.
Did you implement your own PID controller for stabilization?
That's usually where things get interesting — tuning the
gains without it oscillating to death.