With the prospect of delivery drones firmly on the horizon, the challenges of developing reliable quadcopters for such a service are being tackled.
One of the biggest issues is the variety of weather conditions that a drone might face when making a delivery. Currently sending out a drone in harsh weather would be a matter of hoping for the best, but researchers at Massachusetts Institute of Technology (MIT) believe they have developed a solution.
The team have created an algorithm that enables a drone to keep an eye on its own “health” while in flight and take action as necessary.
The drone can monitor its fuel levels, and watch out for damage to its propellers, cameras and sensors. If a problem is found, the drone can take an alternative route that includes a charging station, or select another action to minimise potential damage.
Such a self-monitoring system is key to the commercial viability of drone delivery, because it will help to ensure packages actually arrive at their intended destination.
“With something like package delivery, which needs to be done persistently over hours, you need to take into account the health of the system,” explained Ali-akbar Agha-mohammadi, an MIT Department of Aeronautics and Astronautics postdoc.
The researchers tested the technology to determine if it could impact on the rate of delivery success, with impressive results.
“Interestingly, in our simulations, we found that, even in harsh environments, out of 100 drones, we only had a few failures,” said Agha-mohammadi.
However, a typical delivery drone would be likely to make several stops at different addresses while out and about, creating potential issues that could hinder the success of deliveries.
To resolve this, the researchers also developed a route-planning system that will determine the most efficient path to take to conserve fuel and avoid potential danger spots.
This is determined by considering all the possible options, and determining potential risks from different environments.
“Imagine a huge tree of possibilities, and a large chunk of leaves collapses to one leaf, and you end up with maybe 10 leaves instead of a million leaves,”said Agha-mohammadi.
“Then you can … let this run offline for say, half an hour, and map a large environment, and accurately predict the collision and failure probabilities on different routes.”
This could have a dramatic effect on the efficiency of drone deliveries, and could ultimately be very important to their success as a commercial offering.
There is much more to be done before drones can be used for delivery, however the research team, which is partly funded by Boeing, plans to progress to working with delivery packages, which would be affixed to drones using custom electromagnets.
“We believe in the near future, in a lab setting, we can show what we’re gaining with this framework by delivering as many packages as we can while preserving health,” said Agha-mohammadi.
“Not only the drone, but the package might be important, and if you fail, it could be a big loss.”
Perhaps before long we really will be able to receive Amazon deliveries by drone.