Experimental Evaluation of an Observer-based Controller for an Unmanned
Aerial Vehicle in Reforestation Activities
Abstract
Reforestation is pivotal in mitigating climate change, preserving
biodiversity, and safeguarding ecosystems. Precision reforestation
implies efficiently using materials and human resources to conduct this
intensive task. In this sense, using unmanned aerial vehicles (UAVs),
also known as drones, improves the accuracy of dispensed seeds while
increasing coverage and reducing labor. However, drone-based
reforestation still presents technological challenges that need to be
addressed. An important challenge is the presence of disturbances during
flights due to environmental conditions, primarily unexpected wind, and
the unavoidable loss of mass presented by the vehicle caused by the
dispensing task. This paper evaluates the use of an observer-based
controller to reject the particular disturbances caused by the sowing
activity. Through meticulous experimentation and analysis, the study
demonstrates the observer’s adeptness in mitigating external
disturbances, thereby enhancing the precision and stability of UAV
operations. This technological advancement holds promise for diverse
practical applications and has implications for environmental
conservation efforts, particularly reforestation. The obtained
experimental results confirm the viability of the proposed controller
and observer framework, highlighting its potential to improve the
robustness of environmental monitoring, conservation, and sustainable
resource management practices.