To be useful, drones need to be quick. Because of their limited battery life, they must complete whatever task they have — searching for survivors on a disaster site, inspecting a building, or delivering cargo — in the shortest possible time. And they may have to do it by going through a series of waypoints like windows, rooms, or specific locations to inspect, adopting the best trajectory and the right acceleration or deceleration at each segment.
The best human drone pilots are very good at doing this and have so far outperformed autonomous systems in drone racing. Researchers have created an algorithm that can find the quickest trajectory to guide a quadrotor — a drone with four propellers — through a series of waypoints on a circuit. The novelty of the algorithm is that it generates time-optimal trajectories that fully consider the drones’ limitations.
Previous work relied on simplifications of either the quadrotor system or the description of the flight path and thus they were sub-optimal. Rather than assigning sections of the flight path to specific waypoints, the algorithm tells the drone to pass through all waypoints but not how or when to do that.
The algorithm and two human pilots flew the same quadrotor through a race circuit. They employed external cameras to precisely capture the motion of the drones and in the case of the autonomous drone, to give real-time information to the algorithm on where the drone was at any moment. To ensure a fair comparison, the human pilots were given the opportunity to train on the circuit before the race.
All of the algorithm’s laps were faster than the human ones and the performance was more consistent. Once the algorithm has found the best trajectory, it can reproduce it faithfully many times, unlike human pilots.
Before commercial applications, the algorithm will need to become less computationally demanding, as it now takes up to an hour for the computer to calculate the time-optimal trajectory for the drone. Also, the drone currently relies on external cameras to compute where it is at any moment. In future work, the scientists want to use onboard cameras. The algorithm could be used in package delivery, inspection, and search and rescue.
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