Scientists at TU Delft have created a groundbreaking algorithm that enables autonomous drones to work together to transport heavy payloads, revolutionizing applications in agriculture, construction and rescue operations.
Scientists at Delft University of Technology in the Netherlands have developed an innovative algorithm that allows multiple autonomous drones to collaborate in transporting heavy payloads, even in difficult weather conditions.
This development, published in the journal Science Robotics, could revolutionize various industries by enabling drones to efficiently perform tasks like reaching hard-to-access infrastructure, transporting building materials to remote areas, and aiding in rescue missions.
“A single drone can only carry a very limited load,” Sihao Sun, a robotics researcher at TU Delft, said in a news release. “This makes it hard to use drones for tasks like delivering heavy building materials to remote areas, transporting large- amount of crops in mountainous regions, or assisting in rescue missions.”
The new system devised by the TU Delft team involves several drones connecting to a payload via cables, enabling them to lift and transport significantly heavier loads. By constantly adjusting their positions, the drones can control the payload’s orientation, ensuring precise placement even in complex settings.
Fast Coordination Is Key
“The real challenge is the coordination,” Sun added. “When drones are physically connected, they have to respond to each other and to external disturbances like sudden movements of the payload in rapid motions. Traditional control algorithms are simply too slow and rigid for that.”
To address this, the researchers developed a fast, flexible and robust algorithm that adapts to changing payloads and external forces without the need for sensors on the payload itself. This design enhances the system’s practicality for real-world applications.
In their controlled lab experiments, the team built custom quadrotors and subjected them to various tests, including navigating through obstacles, simulating wind conditions with a fan, and transporting a dynamic payload like a moving basketball.
The results were promising — showing that the drones, once given a destination, could autonomously navigate and adapt to challenges along the way.
“You just tell them where to go, and they figure out the rest,” Sun added.
Real-World Applications in Sight
At present, the system relies on external motion capture cameras for indoor testing, limiting its immediate applicability to outdoor environments.
However, the team aims to refine the technology for real-world deployment, with future applications envisioned in search and rescue operations, agriculture, and remote construction.
Source: Delft University of Technology