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Learning acrobatic maneuvers for quadrocopters
Have you ever seen those videos of quadrocopters performing acrobatic maneuvers?
The latest paper on the Autonomous Robots website presents a simple method to make your robot achieve adaptive fast open-loop maneuvers, whether it’s performing multiple flips or fast translation motions. The method is thought to be straightforward to implement and understand, and general enough that it could be applied to problems outside of aerial acrobatics.
Before the experiment, an engineer with knowledge of the problem defines a maneuver as an initial state, a desired final state, and a parameterized control function responsible for producing the maneuver. A model of the robot motion is used to initialize the parameters of this control function. Because models are never perfect, the parameters then need to be refined during experiments. The error between the robot’s desired state and its achieved state after each maneuver is used to iteratively correct parameter values. More details can be found in the figure below or in the paper.
Method to achieve adaptive fast open-loop maneuver. p represents the parameters to be adapted, C is a first-order correction matrix, γ is a correction step size, and e is a vector of error measurements. (1) The user defines a motion in terms of initial and desired final states and a parameterized input function. (2) A first-principles continuous-time model is used to find nominal parameters p0 and C. (3) The motion is performed on the physical vehicle, (4) the error is measured and (5) a correction is applied to the parameters. The process is then repeated.
Experiments were performed in the ETH Flying Machine Arena which is equipped with an 8-camera motion capture system providing robot position and rotation measurements used for parametric learning.
