Drones are widely used today for disaster response, package delivery, and military operations. Now, a smaller and more specialized type is gaining attention: nanodrones.
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Also known as Nano Aerial Vehicles (NAVs), nanodrones are a subset of unmanned aerial vehicles (UAVs) that weigh under 100 grams and span just a few centimeters. Their small size makes them well-suited for operating in confined, GPS-denied spaces like tunnels, pipelines, and potentially even inside the human body.1-3
Nanodrones are still in early stages of development, but progress is happening in materials, onboard computing, navigation systems, and control algorithms. These compact flyers rely on lightweight sensors, efficient power sources, and advanced software to stay stable and carry out tasks with minimal external infrastructure.
For instance, research from IIT Bombay shows that with off-board cameras and custom control software, nanodrones can navigate indoor environments at relatively low cost.3
Concepts once seen as sci-fi are now under serious investigation in research labs, with real-world applications beginning to take shape across medicine, industry, and defense.
Medical Applications
Healthcare is one of the most developed areas for nanodrone research. The idea of using them for targeted drug delivery is becoming more practical. A nanodrone could carry medication directly to a specific type of cell or tissue, improving treatment accuracy and reducing side effects.4
Although not yet used in patients, research is moving quickly. Technologies like microfluidics, biosensors, and new materials are helping these small devices detect biological signals and deliver drugs more precisely. Some nanodrones can be guided by magnetic fields or light through environments that mimic blood vessels.4
Nanodrones may also help with diagnosis. They could collect samples of fluid or tissue on a very small scale, which could improve early detection of diseases such as cancer or neurological conditions.5
Some designs go further. Bio-hybrid nanodrones, combining synthetic components with biological cells (like red blood cells or platelets), can “camouflage” themselves from the immune system, circulate longer, and deliver drugs more effectively to disease sites. These designs can carry imaging agents, enabling them to act as diagnostic tools as well.5
To see how research labs are building and testing nano-scale UAVs, this talk from UPenn’s GRASP Lab offers a practical look at AI-driven control systems and modular hardware:
Open Source Nano-UAVs - Design, Applications, and Potential - Fernando Cladera Ojeda, Devster, UPenn
Industry, Environment, and Defense
Industrial Inspection
Nanodrones are useful for checking areas that are hard to access or unsafe, such as inside pipelines, engines, or cleanrooms. They can do this without shutting down equipment. Their small size allows inspections without disrupting operations. For example, they've been used to inspect turbine blades and semiconductor facilities with less risk of contamination and more uptime.6
In collaboration with Shimizu Corporation, a leading construction and civil engineering firm based in Tokyo, researchers at Carnegie Mellon University's (CMU) Robotics Institute developed a prototype drone for inspecting bridges and other infrastructure, as reported on CMU’s website.
As part of this initiative, the team introduced a new method that significantly enhances the accuracy of automated systems in detecting and monitoring cracks in reinforced concrete.
Environmental Monitoring
Nanodrones are also being tested for monitoring pollution in air, soil, and water. They can reach locations that are difficult or unsafe for people. Their ability to fly low and slow allows for more granular data collection than satellite or traditional aerial methods.7
A recent study by Srivastava et al. demonstrates that drone-derived imagery combined with digital photogrammetry can accurately estimate tree heights and delineate individual tree crowns. The approach offers a cost-effective, scalable, and efficient alternative to traditional field-based surveys and expensive LiDAR methods.
It also opens pathways for the application of machine learning to further enhance vegetation classification and biomass estimation. Overall, the study validates drone-based remote sensing as a valuable tool for sustainable forest management and resource planning.8
Defense and Surveillance
Due to their stealth, nanodrones are being considered for close-quarters reconnaissance and surveillance. Their ability to maneuver silently in buildings or dense terrain gives them an edge in both military and law enforcement contexts. Some prototypes are equipped with miniature cameras and wireless transmitters to relay real-time footage.9
In theory, nanodrones could infiltrate buildings, scan devices, or eavesdrop without detection. While true autonomous spy nanodrones remain largely theoretical, DARPA and other defense research bodies have explored the use of insect-sized microdrones and the concept of nanoscale surveillance dust.
In 2020, DARPA started a program to study how nano-air-vehicles could use light and heat to move in low-visibility settings. The goal is to improve sensing.
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Supporting Technologies
Localization and Navigation
Localization is one of the main technical challenges for nanodrones in environments where GPS doesn’t work, such as indoors or underground. Recent research shows that using a single camera, open-source algorithms, and external computing, nanodrones can determine their position with an average error of just 3.1 cm. The total setup.10
Research by Palossi et al. shows that deep neural networks (DNNs) can run on very low-power chips to support onboard visual navigation. Some systems now use 64-milliwatt DNN engines to maintain stable flight while using minimal energy. This is important for keeping drones airborne longer and improving flight safety.11
Materials and Flight Systems
New materials are making nanodrones lighter and more durable. Improvements in batteries and micro-electromechanical systems (MEMS) are increasing flight time and sensor range without adding bulk. Some researchers are also testing magnetic actuators and wing designs based on insects to reduce size further.12
Not Quite Ready for Takeoff: What’s Holding Nanodrones Back
Nanodrones show promise, but several technical and practical challenges still limit their broader use.
One major issue is power and endurance. Most nanodrones can only fly for a few minutes due to the size and capacity of current batteries. Improving energy efficiency and developing compact power sources will be critical for longer and more useful deployments.10
There’s also a trade-off between size and onboard computing. Smaller drones have limited space for processors and sensors. Offloading tasks to external systems can help, but it adds delay and complexity. Nanodrones are also more affected by wind, temperature changes, and electromagnetic interference, which can reduce performance in real-world conditions.6,10
Navigation and communication remain difficult in environments without GPS, such as indoors or underground. These scenarios often require external equipment or specialized setups. Ethical and regulatory concerns are also important, particularly around surveillance, privacy, and safety, as these devices become more capable and widely available.10,13
Looking ahead, researchers are focusing on making nanodrones more autonomous and able to work in groups. With improved machine learning, drones could adapt to changing conditions and make real-time decisions without constant human input.13
Digital twin systems are being tested to simulate the drone’s environment and guide behavior in real time. Swarm technology may allow multiple nanodrones to collaborate on tasks like disaster response or internal equipment inspection.13
In healthcare, moving from lab research to clinical trials will depend on safety testing and regulatory approval. In other fields, progress in low-power computing, sensors, and localization will continue to expand what nanodrones can do.
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References and Further Reading
1. Crupi, L.; Giusti, A.; Palossi, D. In High-Throughput Visual Nano-Drone to Nano-Drone Relative Localization Using Onboard Fully Convolutional Networks, 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE: 2024; pp 5345-5351. https://ieeexplore.ieee.org/abstract/document/10611455
2. Ostovar, I. Nano-Drones: Enabling Indoor Collision Avoidance with a Miniaturized Multi-Zone Time of Flight Sensor. Politecnico di Torino, 2022. https://webthesis.biblio.polito.it/23497/
3. Singh, S.; Kumar, A.; Chemban, F. P.; Fernandes, V.; Penubaku, L.; Arya, K., Vision-Based Indoor Localization of Nano Drones in Controlled Environment with Its Applications. arXiv preprint arXiv:2412.08757 2024. https://doi.org/10.48550/arXiv.2412.08757
4. Oigbochie, A.; Odigie, E.; Adejumo, B., Importance of Drones in Healthcare Delivery Amid a Pandemic: Current and Generation Next Application. Open Journal of Medical Research (ISSN: 2734-2093) 2021, 2, 01-13. https://doi.org/10.52417/ojmr.v2i1.187
5. Kishore, C.; Bhadra, P., Targeting Brain Cancer Cells by Nanorobot, a Promising Nanovehicle: New Challenges and Future Perspectives. CNS & Neurological Disorders-Drug Targets-CNS & Neurological Disorders) 2021, 20, 531-539. https://www.benthamdirect.com/content/journals/cnsnddt/10.2174/1871527320666210526154801
6. Palaniappan, D.; Premavathi, T.; Jain, R.; Parmar, K. J., Drones in Manufacturing and Industrial Applications. In Computer Vision and Edge Computing Technologies for the Drone Industry, IGI Global Scientific Publishing: 2025; pp 61-88. https://www.igi-global.com/chapter/drones-in-manufacturing-and-industrial-applications/378908
7. Burgués, J.; Marco, S., Environmental Chemical Sensing Using Small Drones: A Review. Science of the total environment 2020, 748, 141172. https://www.sciencedirect.com/science/article/pii/S004896972034701X
8. Srivastava, S. K.; Seng, K. P.; Ang, L. M.; Pachas, A. N. A.; Lewis, T., Drone-Based Environmental Monitoring and Image Processing Approaches for Resource Estimates of Private Native Forest. Sensors 2022, 22, 7872. https://www.mdpi.com/1424-8220/22/20/7872
9. Abed, M. S.; Jawad, Z. A., Nanotechnology for Defence Applications. In Nanotechnology for Electronic Applications, Springer: 2022; pp 187-205. https://link.springer.com/chapter/10.1007/978-981-16-6022-1_10
10. Chang, Y.; Cheng, Y.; Manzoor, U.; Murray, J., A Review of Uav Autonomous Navigation in Gps-Denied Environments. Robotics and Autonomous Systems 2023, 170, 104533. https://www.sciencedirect.com/science/article/pii/S0921889023001720
11. Palossi, D.; Loquercio, A.; Conti, F.; Flamand, E.; Scaramuzza, D.; Benini, L., A 64-Mw Dnn-Based Visual Navigation Engine for Autonomous Nano-Drones. IEEE Internet of Things Journal 2019, 6, 8357-8371. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8715489
12. Bao, X.; Dargent, T.; Grondel, S.; Paquet, J.-B.; Cattan, E., Improved Micromachining of All Su-8 3d Structures for a Biologically-Inspired Flying Robot. Microelectronic Engineering 2011, 88, 2218-2224. https://www.sciencedirect.com/science/article/pii/S0167931711000906?via%3Dihub
13. Niculescu, V.; Lamberti, L.; Conti, F.; Benini, L.; Palossi, D., Improving Autonomous Nano-Drones Performance Via Automated End-to-End Optimization and Deployment of Dnns. IEEE Journal on Emerging and Selected Topics in Circuits and Systems 2021, 11, 548-562. https://ieeexplore.ieee.org/abstract/document/9606685
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