Experimental Evaluation of an Observer-Based Controller for an Unmanned Aerial Vehicle in Reforestation Activities

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.