Tuning of Drone PD Controller Parameters for Medical Supplies Delivery
Azin Shamshirgaran, Hamed Javidi, Dan Simon
TL;DR
This paper explores the use of evolutionary algorithms for multi-objective optimization to tune drone PD controller parameters, enhancing medical supplies delivery during pandemics.
Contribution
It introduces a novel approach combining evolutionary algorithms with PD controller tuning for drones in medical delivery applications.
Findings
Effective parameter tuning for drone PD controllers achieved
Improved path-following accuracy demonstrated
Potential for reducing human contact in pandemics
Abstract
During the COVID-19 pandemic and similar outbreaks in the future, drones can be set up to reduce human interaction for medical supplies delivery, which is crucial in times of pandemic. In this short paper, we introduce the use of two evolutionary algorithms for multi-objective optimization (MOO) and tuning the parameters of the PD controller of a drone to follow the 3D desired path.
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Taxonomy
TopicsRobotic Path Planning Algorithms · UAV Applications and Optimization · Distributed Control Multi-Agent Systems