Anton Louise P. De Ocampo^*

Revue Internationale de Géomatique, Vol.34, pp. 731-749, 2025, DOI:10.32604/rig.2025.066185 - 10 October 2025

Abstract The effects of climate change are becoming more evident nowadays, and the environmental stress imposed on crops has become more severe. Farmers around the globe continually seek ways to gain insights into crop health and provide mitigation as early as possible. Phenotyping is a non-destructive method for assessing crop responses to environmental stresses and can be performed using airborne systems. Unmanned Aerial Systems (UAS) have significantly contributed to high-throughput phenotyping and made the process rapid, efficient, and non-invasive for collecting large-scale agronomic data. Because of the high complexity and cost of specialized equipment used in… More >

Pavlo Mykytyn^1,2,*, Marcin Brzozowski¹, Zoya Dyka^1,2, Peter Langendoerfer^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1019-1050, 2024, DOI:10.32604/cmes.2023.029075 - 17 November 2023

Abstract The application field for Unmanned Aerial Vehicle (UAV) technology and its adoption rate have been increasing steadily in the past years. Decreasing cost of commercial drones has enabled their use at a scale broader than ever before. However, increasing the complexity of UAVs and decreasing the cost, both contribute to a lack of implemented security measures and raise new security and safety concerns. For instance, the issue of implausible or tampered UAV sensor measurements is barely addressed in the current research literature and thus, requires more attention from the research community. The goal of this… More >

Rana Javed Masood¹, DaoBo Wang¹, Zain Anwar Ali², Muhammad Anwar²

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 295-304, 2019, DOI:10.31209/2018.100000009

Abstract In this article, adaptive hybrid control scheme is proposed for controlling the position of a coaxial tri-rotor unmanned aerial system (UAS) in the presence of input saturation and external wind disturbance. The adaptive hybrid controller consists of model reference adaptive control with integral feedback (MRACI) and proportional integral derivative (PID) controller. The adaptive controller deals with the flight dynamics uncertainties and PID controller is used for tuning the gains of MRACI whereas the stability of system is verified by Lyapunov stability criterion. The integrator improves the order of the system thereby improving the convergence rate… More >