Excellent video, I love how well you're presenting the thought paterns of your algorithms. I hope you make more of these videos! I do want to make a comment about Pure Pursuit which I have avoided making for a long time, but I think paired with your great presentation will be worthy for others to consider. Pure Pursuit is not meant to be used with a fixed "circle". It is an algorithm that should take physical limitation of what the robot can do under consideration if you scale the radius of the circle to the maximum turning radius for your given speed in order to avoid slipping. It can be tuned to be a true motion profiling system in that you set up a profile of the limitation of what the robot can do for your speed and adjust the path accordingly. Proper use of PP is to scale the circle with speed and then determine if you are going to hit any obstacle along the way, if you are then you need to slow down. It thus generates the fastest movement you can possibly do at all times and actively adjust speed as required. I think in the absence of a speed profile/model, this bezier curve solution is an outstanding improvement and probably much simpler/practical for most teams.

Kaden, thanks for an amazing season. Your work is truly excellent.

Yeah, when running a 3 odo setup you generally want to use the odo for the delta heading because it has a much higher precision than the imu for those smaller movements. That's why you use arcs for the entirety of that. Additionally, if you are finding that there is drift then you can do some sensor fusion to gradually feed in the imu to get the accuracy from that and the precision from the odo.

Awesome stuff!

17:33 Yeah curvature is S=R*theta so in this case you can say that dS=R*dtheta. In other words the forward velocity equals the radius times the rotational velocity. You can find rotational velocity by taking the derivative of: d(theta) = d(arctan(dy/dx)) = 1/(1 + (dy/dx)^2)*(ddy*dx-ddx*dy)/dx^2. This then simplifies to: dTheta = (ddy*dx-ddx*dy)/(dx^2+dy^2) then R = dS/dTheta and dS is speed ie (dx^2 + dy^2)^0.5 so you get: r = (dx^2 + dy^2)^0.5/((ddy*dx-ddx*dy)/(dx^2+dy^2)) r = (dx^2 + dy^2)^1.5/(ddy*dx-ddx*dy) Hope this helps people understand how this equation actually is derived

one issue with bezier curves is that is hard to interpolate distances nicely, so it kinda sucks for that, but its the best choice still

Darn!!!!

wow, how did you learn about odometry and bezier curves and all this? I hope to one day become a god coder like yourself.

how did you decide what point in the path to follow at a given time? Is it time-based or position-based or something else?

Could you explqin more about the scalar vect and the PID for the favored drive direction?

at 0:31 you say 2 wheel odometry but there are 8 wheels on the bottom of your robot??? Also could you explain what is the difference between PID and roadrunner?

Bézier than what!?!?