MIT researchers have developed an algorithm that will let drones monitor their own health during deliveries.
To ensure safe, timely, and accurate delivery, drones would need to deal with a degree of uncertainty in responding to factors such as high winds, sensor measurement errors, or drops in fuel. But such “what-if” planning typically requires massive computation, which can be difficult to perform on the fly.
Now MIT researchers have come up with a two-pronged approach that significantly reduces the computation associated with lengthy delivery missions. The team first developed an algorithm that enables a drone to monitor aspects of its “health” in real time. With the algorithm, a drone can predict its fuel level and the condition of its propellers, cameras, and other sensors throughout a mission, and take proactive measures — for example, rerouting to a charging station — if needed.
The researchers also devised a method for a drone to efficiently compute its possible future locations offline, before it takes off. The method simplifies all potential routes a drone may take to reach a destination without colliding with obstacles.
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