Magnisketch Drone Control

Fuente: arXiv
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Bibliographic Details
Main Authors: Kline, Ashley, Elangovan, Abirami, Escandon, Dominique, Wade, Scott, Gupta, Aatish
Format: Preprint
Published: 2024
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author Kline, Ashley
Elangovan, Abirami
Escandon, Dominique
Wade, Scott
Gupta, Aatish
author_facet Kline, Ashley
Elangovan, Abirami
Escandon, Dominique
Wade, Scott
Gupta, Aatish
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2412_10670
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Magnisketch Drone Control
Kline, Ashley
Elangovan, Abirami
Escandon, Dominique
Wade, Scott
Gupta, Aatish
Robotics
Systems and Control
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.
title Magnisketch Drone Control
topic Robotics
Systems and Control
url https://arxiv.org/abs/2412.10670