Drones sense and avoid obstacles and other drones in multiagent system
Feb. 04, 2025.
2 mins. read.
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MIT engineers have found a new way to train multiagent systems where lots of units like drones work together safely.
Drone shows are becoming a big hit for their light displays in the sky. These shows use many drones, each flying a set path to make beautiful patterns. But if a drone has a problem, it can be dangerous for people below.
Drone shows use what engineers call “multiagent systems,” where lots of drones work together. These systems need good safety checks, but they’re hard to manage. Now, MIT engineers have found a new way to train these systems. They train a few drones to safely move around each other, and this training can then work for thousands more.
The method, called GCBF+, looks at how much each drone can see around it, or its “sensing radius.” It then plans safe paths for drones to follow without crashing into each other or other things. The drones learn to keep a safe distance, or “safety margin,” from everything around them.
In real tests, the team used small drones called Crazyflies. They made these drones switch places in the air and land on moving robots, all while avoiding each other. In computer tests, this method scaled up to thousands of drones, showing it could work for big shows or other multiagent tasks.
Applications to more autonomous robots and self-driving cars
This new approach could be used in many places where safety is key, like robot warehouses or self-driving cars. It makes sure each drone or robot can do its job safely, even when things change around them.
“Using our framework, we only need to give the drones their destinations instead of the whole collision-free trajectory,” says research leader Chuchu Fan in an MIT press release, “and the drones can figure out how to arrive at their destinations without collision themselves.”
The engineers have described the methods and results of this study in a paper published in IEEE Transactions on Robotics.
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