MIT researchers have developed a low-power system called MiFly that enables drones to determine their position in 6D space, even in dark and indoor environments. This breakthrough has significant implications for the use of autonomous drones in applications such as warehouse inventory management.
MIT researchers have made a significant step towards autonomous drone navigation with the development of a low-power system that enables drones to determine their position in 6D space, even in dark and indoor environments. The system, called MiFly, utilizes radio frequency waves reflected by a single tag placed in the environment to self-localize the drone.
Autonomous drone navigation utilizes advanced sensors and algorithms to enable drones to fly independently, without human intervention.
This technology relies on GPS, accelerometers, and gyroscopes to determine the 'position, velocity, and orientation' of the drone's position.
Autonomous drones can navigate through obstacles, adapt to changing environments, and perform complex tasks with high precision.
According to a report by 'MarketsandMarkets', the autonomous drone market is expected to grow from $1.4 billion in 2020 to $13.8 billion by 2025, at a CAGR of 47.3%.
Autonomous drones have applications in industries such as agriculture, construction, and surveillance.
The Challenge of Indoor Navigation
Most current drones rely on GPS for navigation, which is not effective indoors. Computer vision and lidar techniques are also unreliable in dark environments or rooms with plain walls or repetitive features. This limitation hinders the use of autonomous drones in applications such as warehouse inventory management, where drones need to navigate through large spaces.
The MiFly System
MiFly uses a backscatter tag that reflects millimeter wave signals sent by the drone’s onboard radar. The tag is designed to add a small frequency to the signal it scatters back to the drone, allowing the reflections from the surrounding environment and the tag to be separated. This enables the drone to calculate distance measurements using only one tag.
Backscatter technology is a non-invasive, low-power method of detecting and analyzing objects.
It works by bouncing radio waves off an object to determine its size, shape, and composition.
This technique is commonly used in security screening, medical imaging, and industrial inspection.
Backscatter technology offers high-resolution images without the need for physical contact or ionizing radiation.
Its applications are expanding into various fields, including baggage scanning, food safety monitoring, and materials analysis.
Dual-Polarization and Dual-Modulation Architecture
To compute the drone’s location, MiFly employs a dual-polarization and dual-modulation architecture. The system uses two off-the-shelf radars mounted on the drone, with one horizontal and one vertical polarization. This setup allows the drone to isolate the separate signals sent by each radar and reduces interference.
Dual-polarization technology is a radar innovation that enables the simultaneous transmission and reception of multiple polarization signals.
This advancement improves weather forecasting accuracy by distinguishing between different types of precipitation, such as 'rain, hail, and snow.'
Dual-polarization radars can also detect the intensity and orientation of hydrometeors, providing more detailed information about storm systems.
As a result, dual-polarization technology has become an essential tool for meteorologists and researchers seeking to enhance their understanding of atmospheric phenomena.
Precise Location Estimation
MiFly estimates the full six-degree-of-freedom pose of the drone in only a few milliseconds. The system fuses millimeter wave measurements reflected by the tag with data from the drone’s onboard inertial measurement unit, which measures acceleration and changes in altitude and attitude.
Results and Future Research
The researchers conducted hundreds of flight experiments with real drones in indoor environments and achieved high accuracy consistently across all environments, localizing the drone to within 7 centimeters. The system was also nearly as accurate in situations where the tag was blocked from the drone’s view. The researchers plan to conduct further research by incorporating MiFly into an autonomous navigation system, enabling a drone to decide where to fly and execute a flight path using millimeter wave technology.
Funding and Future Applications
This research is funded, in part, by the National Science Foundation and the MIT Media Lab. The infrastructure and localization algorithms developed for this work provide a strong foundation for future commercial applications of MiFly.
