Autonomous Drifting

I just purchased new tires for my 2004 Toyota Highlander, which made me cringe a little bit at the rubber being chewed up in this video. Otherwise, it’s awesome 🙂

Chris Gerdes’s lab at Stanford has been working on autonomous donuts and drifting for a few years. Now they’ve partnered with Toyota Research Institute.

I imagine this work requires incredibly accurate state estimation and motion control. The former senses when when the vehicle has crossed boundaries between different states, such as “traction” and “side-slip.” These states are what an engineer or mathematician would call “non-linear.” That’s basically just a mathematical way of saying what most drivers intuitively know — the vehicle starts to handle much differently when it’s in a skid.

The motion controller must then be tuned for several different states, and respond appropriately as the vehicle transitions between states.

I might also imagine that a very finely tuned simulator, modeling the physical components of the vehicle, comes into play.

All of this is a ways away from the more common problems that self-driving cars face, like object tracking and detection.

But high-performance state estimation is necessary for both map-less driving and autonomous flight. Even though this is a car, I bet a lot of what they’re learning could translate to airborne vehicles.

The motion control advances here might eventually allow autonomous vehicles to safely and comfortably travel at higher speeds than humans have ever been able to handle.

And it’s also just cool to watch 😉

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