For the first time an autonomously flying quadrotor has outperformed two human pilots in a drone race. The success is based on a novel algorithm that calculates time-optimal trajectories that fully consider the drones' limitations.
From:
University of Zurich
July 21, 2021 -- 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, 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.
Algorithm outperforms professional
pilots
The best human drone pilots are very
good at doing this and have so far always outperformed autonomous systems in
drone racing. Now, a research group at the University of Zurich (UZH) has
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.
"Our drone beat the fastest lap of two world-class human pilots on an
experimental race track," says Davide Scaramuzza, who heads the Robotics
and Perception Group at UZH and the Rescue Robotics Grand Challenge of the NCCR
Robotics, which funded the research.
"The novelty of the algorithm is
that it is the first to generate time-optimal trajectories that fully consider
the drones' limitations," says Scaramuzza. Previous works relied on
simplifications of either the quadrotor system or the description of the flight
path, and thus they were sub-optimal. "The key idea is, rather than
assigning sections of the flight path to specific waypoints, that our algorithm
just tells the drone to pass through all waypoints, but not how or when to do
that," adds Philipp Foehn, PhD student and first author of the paper.
External cameras provide position
information in real-time
The researchers had the algorithm and
two human pilots fly 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. But
the algorithm won: all its laps were faster than the human ones, and the
performance was more consistent. This is not surprising, because 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, at the moment, the drone relies on external cameras to compute
where it was at any moment. In future work, the scientists want to use onboard
cameras. But the demonstration that an autonomous drone can in principle fly
faster than human pilots is promising. "This algorithm can have huge
applications in package delivery with drones, inspection, search and rescue,
and more," says Scaramuzza.
https://www.sciencedaily.com/releases/2021/07/210721142013.htm
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