New algorithm lets autonomous drones work together to transport heavy, changing payloads
Scientists at TU Delft in The Netherlands have developed a new algorithm that allows multiple autonomous drones to work together to control and transport heavy payloads, even in windy conditions
Delft University of Technology
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Three drones carry a load together, using the new algorithm developed at TU Delft, The Netherlands
view moreCredit: Sihao Sun
Scientists at TU Delft, The Netherlands, have developed a new algorithm that allows multiple autonomous drones to work together to control and transport heavy payloads, even in windy conditions. Ideal for reaching and maintaining hard-to-reach infrastructure, like offshore wind turbines. With often harsh weather, limited payload capacity and unpredictable contact with the environment, it is difficult for current drones to operate safely and effectively. The results have been published in Science Robotics.
“A single drone can only carry a very limited load,” explains Sihao Sun, robotics researcher at TU Delft. “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.”
To overcome these limitations, the TU Delft team designed a system where multiple drones are connected to a payload via cables, thereby carrying much heavier loads. By adjusting their positions in real time, the drones can not only lift and transport the heavy object but also control its orientation, which is crucial for precise placement in complex environments.
Fast coordination
“The real challenge is the coordination,” says Sun. “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.”
The new algorithm developed by the team is fast, flexible, and robust. It adapts to changing payloads and compensates for external forces without requiring sensors on the payload itself, which is an important advantage in real-world scenarios.
Basketball obstacle course in the lab
“We built our own quadrotors and tested them in a controlled lab environment,” Sun shares. “We used up to four drones at once, added obstacles, simulated wind with a fan, and even used a moving payload like a basketball to test dynamic responses.” The system passed all tests. And because the drones are autonomous, they only need to be given a destination. They navigate independently, adjusting for obstacles and disturbances along the way. “You just tell them where to go, and they figure out the rest”, Sun adds.
Preparing for real-world applications
Currently, the system uses external motion capture cameras for indoor testing, and is therefore not useful in outdoor environments yet. The team hopes to prepare the technology for real-world deployment in the future, with potential applications in search and rescue, agriculture, and remote construction
New algorithm lets autonomous drones work together [VIDEO]
Journal
Science Robotics
Experimental study
Subject of Research
Not applicable
Article Title
Agile and Cooperative Aerial Manipulation of a Cable-Suspended Load
Article Publication Date
29-Oct-2025
Drones could cut travel delays and reduce spoilage of donated blood, new Concordia study shows
Researchers integrated the technology with mobile donation vehicles to create a flexible and time-sensitive collection system
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Amirhossein Abbaszadeh: “Vehicle routing problems are not new to operations research, but the perishability of blood brings a time-sensitive challenge that changes how routes must be planned,”
view moreCredit: Concordia University
Delivering blood from collection sites to labs is a fast-paced, labour-intensive process. Donated blood can deteriorate within a few hours at room temperature, leaving little room to manoeuvre in case of unexpected traffic congestion or other delays between collection sites and blood centres.
But if you can’t get through traffic, you can go over it, thanks to drone technology.
In a study published in the journal Computers & Operations Research, Concordia PhD candidate Amirhossein Abbaszadeh and Hossein Hashemi Doulabi, an associate professor in the Department of Mechanical, Industrial and Aerospace Engineering, present a new optimization model that uses drones to support mobile blood donation vehicles (“bloodmobiles”). The model offers a faster, more efficient and more reliable way to transport donated blood in cities.
Powered by smart logistics
The researchers’ Drone-Aided Mobile Blood Collection Problem is the first integrated framework that coordinates the movements of both bloodmobiles and drones to preserve blood freshness and improve overall system performance.
At its heart is a smart logistics system where bloodmobiles travel to multiple collection sites while drones shuttle between them and a central blood centre. This method eliminates delays caused by traffic and ensures that freshly donated blood reaches the blood centre quickly for processing into its components — such as platelets, which must be separated within six hours.
The researchers achieved this by developing a mixed-integer linear programming model that synchronizes the routes, schedules and collection activities of both bloodmobiles and drones. Because such a large-scale optimization problem is computationally demanding, the team also designed a rolling-horizon-based matheuristic algorithm. This type of algorithm breaks the problem into smaller, more manageable parts, solving sequentially while simultaneously exploring nearby alternatives to find better ones.
“Vehicle routing problems are not new to operations research, but the perishability of blood brings a time-sensitive challenge that changes how routes must be planned,” says Abbaszadeh. “That’s when I thought of using drones.”
Unlike previous studies that treated bloodmobiles and drones as separate systems, this work fully integrates their operations. Drones can take off from, land on or travel aboard bloodmobiles, allowing flexible coordination across multiple collection points without fixed infrastructure.
The model also considers the age of the blood — the time elapsed since donation — as a key optimization factor, rewarding fresher blood deliveries to ensure quality.
Putting the model to the test
The researchers used Quebec City as a real-world case study to test their model. They identified 13 potential collection sites, estimated the number of potential donors at each site and calculated the distance to the nearest blood centre.
“We used Google Maps to calculate the road distance and the most direct flight path since drones don’t need to use roads,” explains Abbaszadeh.
“We performed several analyses using different parameters: What if we used drones that had more load capacity, higher battery capacity or moved at higher speeds? We then compared the drone-aided system to the bloodmobile-only system.”
They found that adding drones to the blood collection fleet significantly reduced transport times. It also increased hourly delivery rates and maintained better consistency in blood freshness.
The authors write that their findings demonstrate the real potential of drone-assisted logistics in healthcare supply chains, particularly in time-critical operations like blood collection. They add that their framework could be adapted to other humanitarian or medical delivery contexts where speed, coordination and freshness are essential.
Read the cited paper: “Drone-Aided Mobile Blood Collection Problem”
Journal
Computers & Operations Research
Method of Research
Computational simulation/modeling
Subject of Research
People
Article Title
Drone-aided mobile blood collection problem: A rolling-horizon-based matheuristic
