The most important element needed for the success of any drone’s task is its quickness in accomplishing it. This is mainly because of their limited battery life. Thus, it is necessary that they complete whatever task present, such as delivering cargo, searching for survivors on a disaster site, or inspecting a building, etc., in the shortest time possible. The problem, however, comes when they also have to dodge wayward points like rooms, windows, or a particular location to investigate. The best solution for such situations is adopting the most suitable trajectory and the correct acceleration and deceleration at each point. Till now, human drone pilots have always come to be more efficient in comparison to autonomous systems in drone racing.
Now, a research group might have brought forth a solution to make autonomous drones more efficient. They have developed an algorithm with the ability to find the most efficient trajectory to guide a quadrotor (a drone with four propellers) across a number of waypoints on a circuit. The newly created algorithm could lead to a great boost in Drones Market as the researchers have managed to makes drones much more efficacious, so much so that their drones successfully overtook the fastest lap of two top human pilots on an experimental race track.
The novel aspect of the algorithm lies in the fact that this is a first where time-optimal trajectories have been generated considering drones’ limitations wholly. The team’s key idea was that instead of assigning a section of the flight path to particular waypoints, the algorithm tells the drone how to pass through the waypoints but not how or when.
To test their development, researchers made the algorithm and two human pilots fly the same quadrotor through an experimental circuit. They made use of cameras to capture all the motions of the drones accurately in the case of an autonomous drone, to receive real-time information on the location of the drone. They ensured the fairness of the competition by providing time to the human pilots to trains on the circuit beforehand. However, the end result shows that the algorithm was first, and all its laps were found to be faster than human-led drones. In addition, the performance of autonomous drones was consistent as well.
Although the algorithm is a huge advancement, it still needs to become less computationally demanding before it is made a commercial application. In the future, the researchers would be using the onboard cameras to understand its location, but for now, the drone relies on external cameras. Nonetheless, the algorithm would be immensely applicable once it is out in package delivery, search and rescue, inspection, and more.
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