Optimizing control of Automated Guided Vehicles
DENSO recently completed proof-of-concept work aimed at optimizing control of Automated Guided Vehicles (AGVs) on their factory floors. These robotic transports move materials around the factory using automated guidance systems. Given the number of AGVs working at a time, striking a balance between smooth control of each machine and collision avoidance while keeping pace with production needs is of paramount importance.
Using the power of hybrid classical-quantum computing, DENSO narrowed down and ranked the optimal number of paths AGVs could take around the factory. Then, they focused on reducing traffic congestion across the ecosystem.
The results were significant: researchers were able to produce solutions that reduced the amount of time each AGV spent waiting for a clear route to open up by an average of 15%, even when focusing on safety over speed.
A success case that opens the doors to applied quantum computing
DENSO worked on this application together with D-Wave and the Tohoku University back in 2019. The result was so amazing that a paper was published on Nature. You can download the paper here on Apply Quantum, or directly here on Nature website.
