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.
Welcome to drone day on the Adafruit blog. Every Monday we deliver the latest news, products and more from the Unmanned Aerial Vehicles (UAV), quadcopter and drone communities. Drones can be used for video & photography (dronies), civil applications, policing, farming, firefighting, military and non-military security work, such as surveillance of pipelines. Previous posts can be found via the #drone tag and our drone / UAV categories.
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