New AI model could streamline operations in a robotic warehouse

However, getting 800 robots to and from their destinations efficiently while keeping them from crashing into each other is no easy task. Their technique divides the warehouse robots into groups, so these smaller groups of robots can be decongested faster with traditional algorithms used to coordinate robots. “We devised a new neural network architecture that is actually suitable for real-time operations at the scale and complexity of these warehouses. For instance, in a warehouse with 800 robots, the network might cut the warehouse floor into smaller groups that contain 40 robots each. For instance, in a warehouse with 800 robots, decongesting a group of 40 robots requires holding the other 760 robots as constraints.