Researchers at the Massachusetts Institute of Technology (MIT) have developed a system that enables drones to determine their position in dark or indoor environments using radio frequency waves. The system, called MiFly, allows drones to self-localize without relying on GPS, which is ineffective indoors, or computer vision and lidar, which struggle in low-light conditions or featureless environments.
MiFly operates using a single small tag placed in the environment, which reflects signals rather than generating its own, allowing for low power consumption. Two off-the-shelf radars mounted on the drone—one horizontally and one vertically—send polarized signals that are reflected by the tag. The system separates these reflections through modulation, allowing the drone to distinguish signals from the tag amid other environmental reflections. The drone then integrates these measurements with data from its onboard sensors to estimate its trajectory and position in six degrees of freedom, accounting for movement in multiple directions as well as rotation.
MIT researchers conducted extensive tests in various indoor environments, including a flight space at the university and tunnels beneath campus buildings. MiFly consistently localized drones to within seven centimeters and remained effective even when the tag was partially obstructed.
The research team includes Associate Professor Fadel Adib, along with co-lead authors Maisy Lam and Laura Dodds, former postdoctoral researcher Aline Eid, and Jimmy Hester, co-founder of Atheraxon, Inc. The findings will be presented at the IEEE Conference on Computer Communications. Future research aims to integrate MiFly into a broader autonomous navigation system to expand its commercial applications.
Figures courtesy the researchers; edited by MIT News
