University of Washington

Smellicopter Begins By Moving To The Left For A Specific Distance. If Nothing Passes A Certain Smell Threshold

University of Washington

Researchers from the University of Washington have developed an autonomous drone which uses a live moth antenna to seek out smells in its surroundings. There is considerable interest in developing drones that could detect chemicals in the air, locating disaster survivors, gas leaks, explosives, narcotics, and other objects of interest. However, most human-made sensors are not sensitive or fast enough for these applications.

The University of Washington engineers worked around this by incorporating a live antenna from a moth to create a drone that can navigate towards smells. “Nature really blows our human-made odour sensors out of the water,” said mechanical engineer and PhD candidate Melanie Anderson. “By using an actual moth antenna with Smellicopter, we’re able to get the best of both worlds: the sensitivity of a biological organism on a robotic platform where we can control its motion.”

Moths use their antennae to detect chemicals in their surroundings and navigate towards food sources or potential mates: “Cells in a moth antenna amplify chemical signals. The moths do it really efficiently – one scent molecule can trigger lots of cellular responses, and that’s the trick. This process is super-efficient, specific, and fast,” said Professor Thomas Daniel, a University of Washington biologist. The researchers used antennae from the Manduca sexta hawkmoth; they placed live moths in the fridge to anaesthetise them before removing an antenna. Once separated from the moth, the antenna remains biologically and chemically active for up to four hours.

The antenna was wired into a circuit, so that the researchers could measure the average signal from its cells. They compared it to a typical human-made sensor by placing both in a wind tunnel and wafting various smells into the tunnel; the antenna reacted and recovered more quickly than the conventional sensor.

The antenna sensor was then incorporated into an open-source quadcopter drone platform which allows users to add custom features, creating Smellicopter. Two plastic fins were attached to the back of the drone to orient it upwards during flight.

The researchers created a “cast and surge” protocol for the drone which mimics how moths search for smells. Smellicopter begins by moving to the left for a specific distance. If nothing passes a certain smell threshold, it moves to the right for the same distance. When it detects an odour, it changes its flying pattern to surge towards the source. Smellicopter is also capable of avoiding obstacles with the help of four infrared sensors, which scan its surroundings 10 times per second. When an object is within 20cm of the drone, it changes direction by moving to the next stage of its cast-and-surge protocol.

“So, if Smellicopter was casting left and now there’s an obstacle on the left, it’ll switch to casting right,” said Anderson. “And if Smellicopter smells an odour but there’s an obstacle in front of it, it’s going to continue casting left or right until it’s able to surge forward when there’s not an obstacle in its path.” In lab-based tests, the drone naturally flew towards smells that moths find interesting, such as floral scents. However, the researchers hope that in future it could be adapted to detect other scents, such as carbon dioxide or the chemical signature of an unexploded device.

“Finding plume sources is a perfect task for little robots like the Smellicopter,” said mechanical engineer Professor Sawyer Fuller. “Larger robots are capable of carrying an array of different sensors around and using them to build a map of their world. We can’t really do that at the small scale.” “But to find the source of a plume, all a robot really needs to do is avoid obstacles and stay in the plume while it moves upwind. It doesn’t need a sophisticated sensor suite for that – it just needs to be able to smell well. And that’s what the Smellicopter is really good at.”

This news was originally published at Eandt