Inspired by a fiddler crab eye, scientists developed an amphibious artificial vision system with a panoramic visual field.
Researchers train a machine-learning model to monitor and adjust the 3D printing process to correct errors in real-time.
With FabO, PhD student Dishita Turakhia wants to empower students to learn digital fabrication by making video game objects and characters come alive.
This robotic system uses radio frequency signals, computer vision, and complex reasoning to efficiently find items hidden under a pile.
MIT scientists unveil the first open-source simulation engine capable of constructing realistic environments for deployable training and testing of autonomous vehicles.
The new design is stackable and reconfigurable, for swapping out and building on existing sensors and neural network processors.
MIT CSAIL scientists created an algorithm to solve one of the hardest tasks in computer vision: assigning a label to every pixel in the world, without human supervision.
For the MIT Schwarzman College of Computing dean, bringing disciplines together is the best way to address challenges and opportunities posed by rapid advancements in computing.
Associate professor and principal investigator with the MIT Schwarzman College of Computing’s Science Hub discusses the future of robotics and the importance of industry-academia collaborations.