Laboratory for Information and Decision Systems (LIDS)

Researchers at MIT have developed an artificial intelligence tool to improve the efficiency of robotic warehouses. The researchers, drawing from their work in moderating traffic congestion, created a deep-learning model that can process information about the warehouse, including robot paths, tasks, and obstacles, to optimize warehouse functionality. By grouping the robots into smaller units, the…

In crowded robotic warehouses, managing hundreds of robots to navigate efficiently and avoid collisions is a complex challenge. This has prompted a group of MIT researchers to create a deep-learning model to tackle the problem. Using AI, the team has developed an innovative model that encapsulates details about the warehouse environment - the robots, planned…

As automated warehouses become increasingly popular in various industries, ensuring the efficiency and safety of hundreds of robots navigating such spaces is a significant challenge. Notably, even top-performing algorithms struggle to keep pace with the demands of e-commerce or manufacturing. To address this, a group of MIT researchers, who use AI to mitigate traffic congestion,…

Navigating hundreds of robots in a warehouse without causing accidents is a growing challenge for many industries, from e-commerce to automotive production. To address this issue, a team of researchers at the Massachusetts Institute of Technology (MIT) has developed an AI-based approach that increases efficiency and reduces congestion. The team devised a deep learning model that…