Nanodrone for Detecting Hazardous Gases in Emergencies

Scientists Santiago Marco and Javier Burgués from the Faculty of Physics of the University of Barcelona and the Institute for Bioengineering of Catalonia (IBEC) have designed and built the Smelling Nano Aerial Vehicle (SNAV), a nanodrone that is capable of detecting hazardous gases in collapsed buildings due to explosions or earthquakes and locating victims in places that are not easy to access.

The experts Javier Burgués and Santiago Marco, from the Faculty of Physics of the University of Barcelona and the Institute for Bioengineering of Catalonia (IBEC). (Image credit: University of Barcelona)

A drone is an aircraft—military or civil—steered using remote control. In this area of technology, which is continuously expanding around its numerous fields of application, nanodrones are operational platforms which weigh less than 250 g.

Illustrated for the first time in an article in the journal Sensors, the SNAV nanodrone weighs 35 g and is engineered to fly and identify gases in multiple scenarios where other technological gadgets cannot easily reach. It comprises nanometric MOX gas sensors that can react to gases such as methane (CH4) or carbon monoxide (CO), and other organic volatile compounds (acetone, ethanol, benzene, etc.), with a detection threshold of sensors of the order of a part per million in volume (ppmv), according to the gas and the used sensor.

Unique when compared with other larger gadgets, SNAV can work in interior spaces. It can cross cracks and holes and can operate in large areas measuring about 160 m2, where the chemical emission source is hidden in areas that are not easy to access such as air duct systems and false ceilings.

SNAV: From Detecting Toxic Gases to Rescuing Victims

This new device would be particularly beneficial in “rescue operations in collapsed buildings due to earthquakes and explosions—SNAV can detect toxic gases and even the compounds unconscious victims inhale—and in a search for drugs or explosives in places which are hard to enter,” notes Santiago Marco, chief researcher at IBEC and member of the Department of Electronic and Biomedical Engineering of the UB, who headed the new research study.

In these circumstances after an explosion or earthquake, rescue teams typically have trained dogs to locate the victims. Thus, the possibility of using autonomous robots in these jobs is an option to keep in mind in the short and long run.

“Terrestrial robots used to focus the searching on the field of chemical signalling-based localization. Today, the option of using nanodrones broadens the ability and quickness of the robots to move within an interior space and overcome obstacles such as stairs,” notes Marco, head of the Research Group Senyal Intelligent per Sistemes sensors en BioEnginyeria (intelligent signaling for sensor systems in bioengineering) UB-IBEC.

How to Overcome the Effect of Turbulences and Navigation Problems

Limitations concerning weight and application of the nanodrone and the negative effects of turbulence of the rotor on the sensor signals are significant inflection spots for the design and technical development of nanodrones such as SNAV. To overcome the undesirable effect of turbulences, which influences the data acquiring process, the UB-IBEC team applied signal procedure methods that help gather valuable information from the sensors in the SNAV.

Another important point is the self-localization of the nanodrone in the action situation. Generally, the control mechanism of drones that fly great distances in open spaces is based on a GPS navigation system. However, this is not a feasible option for devices that fly inside interior spaces.

The new nanodrone has accelometers and gyroscopes that help navigation but without the expected precision for its localization. Therefore, this function is based on a series of six radiofrequency transceivers—located in known positions—and a transceiver put in the same drone. This system allows us to fly the nanodrone to the position we want.

Javier Burgués, study’s first signer and Scientist, UB-IBEC.

New Algorithms Inspired by Animal Behavior

As part of the research, the UB-IBEC team of professionals worked on the SNAV platform, calibrating the sensors and checking its working as well as programming the algorithms for communication, data processing, and robotic navigation. Once the SNAV platform was developed, all robotic navigation trials from SNAV were conducted at Örebro University (Sweden), in partnership with the specialists Víctor Hernández and Achim J. Lilienthal.

Going forward, this research team plans to create bio-inspired navigation algorithms to be based, for example, on insect behavior such as the moth or the mosquito. “Another line we want to work on is the merge of data from multiple gas sensors to increase selectivity towards certain compounds of interest. In this case, researchers would work on experiments in complex scenarios and with chemical interferences,” conclude the specialists Santiago Marco and Javier Burgués.

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