In an enormous robotic warehouse, hundreds of robots zip back and forth, picking up items and delivering them to human workers for packing and shipping. This is becoming an increasingly common scene in various industries, from e-commerce to automotive manufacturing. However, managing these large numbers of robots, ensuring they reach their destinations effectively, and avoiding…
In the growing field of warehouse automation, managing hundreds of robots zipping through a large warehouse is a logistical challenge. Delivery paths, potential collisions and congestion all pose significant issues, making the task a complex problem that even the best algorithms find hard to manage. To solve this, a team of MIT researchers has developed…
In order to improve efficiency in large-scale robotic warehouses, a team of researchers from the Massachusetts Institute of Technology (MIT) have developed a deep learning model which assists in navigating robots to decongest warehouse floors. The way this model works is by splitting the hundreds of robots into smaller, manageable groups which are easier for…
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…
Tomás Vega, MIT alum and CEO of Augmental, found technology a great equalizer when he dealt with a stuttering disorder at a young age. Vega began programming at age 12 and continued to use technology to augment human abilities throughout high school and college. He made it his mission to help people with disabilities live…
Drug efficacy in humans can be heavily influenced by how it interacts with various digestive system transporters. Researchers at the Massachusetts Institute of Technology (MIT), Duke University, and Brigham and Women’s Hospital have developed a method that identifies the interactions between drugs and these transporters. These interactions can potentially result in adverse effects if two…
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…
Researchers from MIT, Brigham and Women’s Hospital, and Duke University have developed a machine-learning, multipronged strategy to identify which transporter proteins a drug uses to navigate through a patient's digestive tract. Knowledge in this area is key to improving drug efficacy and patient safety as drugs using the same transporter proteins can interfere with each…
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,…