A Survey of Medical Drones from Flight Dynamics, Guidance, Navigation, and Control Perspectives

The integration of drones into the medical field has revolutionized healthcare delivery by enabling rapid transportation of medical supplies, organs, and even emergency assistance in remote or disaster-stricken areas. While other survey papers focus on the healthcare supply chain, operations, and medical emergency response aspects, this paper provides a comprehensive review of medical drones from the perspectives of flight dynamics and guidance, navigation, and control (GNC) systems. We first discuss the medical aerial delivery mission requirements and suitable uncrewed aerial system (UAS) configurations. We then address payload container design and optimization, and its effect on supplies and overall flight dynamics. We also explore the fundamental principles of GNC in the context of medical drone operations, highlighting key challenges arising from vibration, air temperature, pressure, and humidity, which affect the quality of medical supplies. The paper examines various GNC algorithms that can mitigate these challenges, as well as the algorithms’ limitations. With these considerations, this survey aims to provide insights into optimizing GNC frameworks for medical drones, emphasizing research gaps and directions to improve real-world healthcare applications.

💡 Research Summary

**
The paper provides a comprehensive survey of medical drones focusing on flight dynamics and guidance, navigation, and control (GNC) systems, addressing a gap in the existing literature that largely concentrates on logistics and emergency response. It begins by outlining the mission requirements unique to medical deliveries: strict time constraints to preserve temperature‑sensitive payloads, long‑range capability, high‑precision landing (often on rooftops or remote clinics), autonomous BVLOS operation, and compliance with civil aviation regulations.

Three primary UAS configurations are examined. Fixed‑wing platforms offer aerodynamic efficiency and high cruise speeds suitable for long‑distance transport but require runways or catapults and lack hover capability. Multirotor (quad‑, hexacopter) systems provide vertical take‑off and landing (VTOL) and precise hovering, making them ideal for short‑range, point‑to‑point deliveries, yet they suffer from limited endurance due to higher power consumption. Hybrid VTOL designs combine the advantages of both, delivering vertical lift for take‑off/landing and efficient forward flight for extended missions, though they introduce added structural weight and more complex control laws.

Payload container design is treated as a critical factor influencing both mission success and flight performance. Three container concepts are discussed: (1) cable‑suspended payloads enable mid‑air release without landing, reducing contamination risk for infectious samples, but introduce a multi‑body dynamic system whose natural frequency depends on cable length. Oscillations increase power demand and can destabilize the vehicle, requiring active damping, real‑time control, and careful placement of the attachment point near the drone’s center of mass. (2) Fixed payloads are rigidly attached, simplifying dynamics and improving stability, yet they limit cargo size and necessitate landing at the delivery site. Design considerations include weight distribution, aerodynamic shaping, and vibration isolation to protect delicate medical items. (3) Temperature‑controlled containers incorporate insulated enclosures, Peltier cooling/heating, phase‑change materials, and active temperature monitoring (e.g., thermocouples, digital loggers). Demonstrated implementations on DJI S900, M1000, and Mavic Air show that temperature can be maintained within clinically acceptable ranges, but the added mass and power draw impact battery endurance.

Environmental influences—wind, turbulence, temperature, humidity, pressure, and vibration—are analyzed for their dual impact on flight dynamics and payload integrity. Low ambient temperature reduces Li‑Po battery capacity, shortening flight time; high temperature accelerates battery aging and can trigger thermal throttling of electronics. Variations in air density affect lift and required rotor speeds, while humidity degrades sensor accuracy and pressure fluctuations perturb aerodynamic models. Vibration, especially in cable‑suspended systems, can compromise temperature‑sensitive biologics such as insulin, necessitating vibration isolation or active control.

The survey then reviews GNC algorithms applicable to medical drones. Classical PID and LQR controllers provide baseline stability but lack robustness to severe disturbances. Adaptive control schemes adjust gains in real time to compensate for changing battery voltage and payload mass. Model Predictive Control (MPC) is highlighted for its ability to handle multi‑objective optimization—balancing trajectory tracking, energy consumption, and payload temperature regulation—within a receding horizon framework, though computational load remains a challenge for onboard processors. Sliding Mode Control (SMC) offers strong disturbance rejection, useful for wind gust mitigation. Emerging reinforcement‑learning (RL) approaches promise autonomous policy generation in highly nonlinear, uncertain environments, yet safety guarantees and sample efficiency are still open issues.

Finally, the authors identify research gaps: (1) Integrated simulation environments that concurrently model aerodynamics, battery electrochemistry, thermal payload dynamics, and atmospheric disturbances; (2) Coordinated multi‑drone load‑sharing and cooperative transport algorithms for oversized or heavy medical cargo; (3) Energy‑aware management of temperature‑controlled containers to minimize impact on flight endurance; (4) Formal verification and certification processes that align GNC designs with evolving aviation regulations for BVLOS medical operations.

In conclusion, the paper underscores that successful medical drone deployment hinges not only on aerodynamic efficiency but also on sophisticated GNC strategies that actively mitigate environmental effects and preserve payload integrity. Addressing the highlighted gaps will be essential to transition medical drones from experimental prototypes to reliable, large‑scale healthcare delivery platforms.