MIT Tailsitter Drone Acrobatics

Post by fisian » Sun, Feb 19, 2023, 7:26 AM UTC

Isamu wrote: post #40

fisian wrote: post #37

Flatness[1] based control is pretty neat. Basically, you can define a trajectory (that is differentiable n-times) and then calculate the state of the system from that. In this case, given the trajectory they could compute the speed, acceleration, jerk and yaw+rate for the tailsitter ahead of time using the model. [1] https://en.wikipedia.org/wiki/Flatness_(systems_theory)

>differential flatness I am trying to understand this a bit better. Do you have other examples?

"Differential flatness" is synonymous to "flatness".

The concept is a bit comparable to inverse kinematics. With inverse kinematics you compute, e.g. the joint angles of a robot arm given its endeffector pose.

While with differential flatness you use the pose trajectory and its derivatives (i.e. how the pose changes over time) to calculate the state trajectory (joint angles, speeds and accelerations for the robot arm example).

Post by robotresearcher » Mon, Feb 20, 2023, 9:40 PM UTC

fwlr wrote: post #7

njoubert wrote: post #6

Ah, tailsitters. Everyone loves the theory, then the practical realities of the takeoff position exposing the entire wing surface to the prevailing wind quickly kills real-world applications. I remember back during the 3D Robotics heyday watching Chris Anderson repeatedly run down to set his tailsitter upright, take a few steps back, only to watch it fall over again.

For vertical takeoff and landing the wing surface is mostly irrelevant, right? Seems like if you gave the rotors a “landing configuration” where they rotated 90 degrees you could lay the wing flat on the ground.

The Harrier, Osprey and the carrier variant of F-35 are real world aircraft that point the thrust vector at the ground for takeoff and landing, then rotate it to the back for forward flight.

Re: MIT Tailsitter Drone Acrobatics

Re: MIT Tailsitter Drone Acrobatics