Magnisketch Drone Control

TL;DR

This paper introduces Magnisketch, a magnetic drawing drone controlled via a novel MPC that incorporates magnetic forces, enabling precise and smooth artistic tasks on a magnetic drawing board.

Contribution

The paper presents a new MPC formulation for UAV magnetic manipulation, integrating magnetic force dynamics for improved control in artistic applications.

Findings

Comparable performance to existing controllers in error metrics

Smoother drawing trajectories achieved with the new controller

Average positional errors of 3.9 cm, 4.4 cm, and 0.5 cm in x, y, z

Abstract

The use of Unmanned Aerial Vehicles (UAVs) for aerial tasks and environmental manipulation is increasingly desired. This can be demonstrated via art tasks. This paper presents the development of Magnasketch, capable of translating image inputs into art on a magnetic drawing board via a Bitcraze Crazyflie 2.0 quadrotor. Optimal trajectories were generated using a Model Predictive Control (MPC) formulation newly incorporating magnetic force dynamics. A Z-compliant magnetic drawing apparatus was designed for the quadrotor. Experimental results of the novel controller tested against the existing Position High Level Commander showed comparable performance. Although slightly outperformed in terms of error, with average errors of 3.9 cm, 4.4 cm, and 0.5 cm in x, y, and z respectively, the Magnasketch controller produced smoother drawings with the added benefit of full state control.