Northwestern University researchers have developed a decentralized algorithm that guarantees collision and congestion avoidance, a key step toward controlling fleets of driverless vehicles.
The researchers applied the algorithm to a simulation of 1,024 robots and to a 100-robot swarm in a laboratory, and in each instance the robots reliably and efficiently converged into a pre-determined shape in less than 60 seconds.
To ensure coordination that avoids collisions and deadlock, the algorithm views the ground under the robots as a grid, and each robot knows its position using technology similar to global positioning systems.
Each robot uses sensors to communicate with its neighbors and interpret nearby grid spaces as vacant or occupied.
Northwestern's Michael Rubenstein said, "By understanding how to control our swarm robots to form shapes, we can understand how to control fleets of autonomous vehicles as they interact with each other."
From Northwestern University McCormick School of Engineering
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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA
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