Bayesian-based learning of flapping-wing kinematics for bio-inspired aerial vehicles

MSc assignment

In this assignment, a framework based on Bayesian-learning will be used to autonomously find the suitable parameters values of an impedance-controlled aerial robot.

By requiring the drone to repeatedly perform a predetermined task in the environment, the learning agent would actively search in the impedance parameters space for the optimal controller gains and profile of the end-effector to perform a high-quality aerial writing task.