Researchers at a US university have developed a new navigation system that they say enables drones to fly indoors – and in the dark.
Drones typically navigate outdoors using GPS, but this doesn’t work in an indoor environment, meaning most of today’s drones would likely struggle to navigate in a dimly-lit or even dark indoor environment, the researchers from the Massachusetts Institute of Technology (MIT) explain.
For indoor navigation, some drones employ computer vision or lidar, but both techniques are unreliable in dark environments, or rooms with plain walls or repetitive features.
However, the MIT team has introduced a new approach that is said to enables a drone to self-localise, or determine its position, in indoor, dark, and low-visibility environments. Such self-localisation is a key step in autonomous navigation.
The researchers developed a system called MiFly, in which a drone uses radio frequency (RF) waves, reflected by a single tag placed in its environment, to autonomously self-localise.
Because MiFly enables self-localisation with only one small tag, which could be affixed to a wall like a sticker, th researchers say it would be cheaper and easier to implement than systems that require multiple tags.
In addition, since the MiFly tag reflects signals sent by the drone, rather than generating its own signal, it can be operated with very low power.
Two off-the-shelf radars mounted on the drone enable it to localise in relation to the tag. Those measurements are fused with data from the drone’s onboard computer, which enables it to estimate its trajectory.
Fadel Adib is an associate professor in MIT’s Department of Electrical Engineering & Computer Science, a director of the Signal Kinetics group in the MIT Media Lab, and senior author of the paper on MiFly.
Adib said: “As our understanding of perception and computing improves, we often forget about signals that are beyond the visible spectrum. Here, we’ve looked beyond GPS and computer vision to millimetre waves, and by doing so, we’ve opened up new capabilities for drones in indoor environments that were not possible before.”
The researchers conducted hundreds of flight experiments with real drones in indoor environments, and found that MiFly consistently localised the drone to within fewer than seven centimetres.
Backscattered signals
To enable drones to self-localise within dark, indoor environments, the researchers decided to use millimetre wave signals. Such waves, which are commonly used in modern radars and 5G communication systems, work in the dark and can travel through everyday materials like cardboard, plastic, and interior walls.
The team set out to create a system that could work with just one tag, so it would be cheaper and easier to implement in commercial environments. To ensure the device remained low power, they designed a backscatter tag that reflects millimetre wave signals sent by a drone’s onboard radar. The drone uses those reflections to self-localise.
But the drone’s radar would receive signals reflected from all over the environment, not just the tag. The researchers surmounted this challenge by employing a technique called modulation. They configured the tag to add a small frequency to the signal it scatters back to the drone.
Laura Dodds, research assistant and co-lead author, said: “Now, the reflections from the surrounding environment come back at one frequency, but the reflections from the tag come back at a different frequency. This allows us to separate the responses and just look at the response from the tag.”
However, with just one tag and one radar, the researchers could only calculate distance measurements. They needed multiple signals to compute the drone’s location.
Rather than using more tags, they added a second radar to the drone, mounting one horizontally and one vertically. The horizontal radar has a horizontal polarization, which means it sends signals horizontally, while the vertical radar would have a vertical polarization.
They incorporated polarization into the tag’s antennas so it could isolate the separate signals sent by each radar.
Maisy Lam, research assistant and co-author of the paper, said: “Polarized sunglasses receive a certain polarization of light and block out other polarizations. We applied the same concept to millimetre waves.”
In addition, the team applied different modulation frequencies to the vertical and horizontal signals, further reducing interference.
This dual-polarization and dual-modulation architecture gives the drone’s spatial location. But drones also move at an angle and rotate, so to enable a drone to navigate, it must estimate its position in space with respect to six degrees of freedom – with trajectory data including pitch, yaw, and roll in addition to the usual forward/backward, left/right, and up/down.
Dodds added: “The drone rotation adds a lot of ambiguity to the millimetre wave estimates. This is a big problem because drones rotate quite a bit as they are flying.”
Six degrees of motion
They overcame these challenges by using the drone’s onboard inertial measurement unit; a sensor that measures acceleration as well as changes in altitude and attitude. By fusing this information with the millimetre wave measurements reflected by the tag, they enable MiFly to estimate the full six-degree-of-freedom pose of the drone in only a few milliseconds.
The team tested a MiFly-equipped drone in several indoor environments, including their lab, the flight space at MIT, and the dim tunnels beneath the campus buildings. The system is said to have achieved high accuracy consistently across all environments, localizing the drone to within seven centimetres in many experiments.
In addition, the system was nearly as accurate in situations where the tag was blocked from the drone’s view. They achieved reliable localization estimates up to six meters from the tag.
That distance could be extended in the future with the use of additional hardware, such as high-power amplifiers, or by improving the radar and antenna design. The researchers also plan to conduct further research by incorporating MiFly into an autonomous navigation system. This could enable a drone to decide where to fly and execute a flight path using millimetre wave technology.
Lam added: “The infrastructure and localization algorithms we build up for this work are a strong foundation to go on and make them more robust to enable diverse commercial applications.”
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