Teaching artificial intelligence to connect senses like vision and touch
MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.
MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.
A new tool for predicting a person’s movement trajectory may help humans and robots work together in close proximity.
Fleet of “roboats” could collect garbage or self-assemble into floating structures in Amsterdam’s many canals.
Signals help neural network identify objects by touch; system could aid robotics and prosthetics design.
Autonomous control system “learns” to use simple maps and image data to navigate new, complex routes.
CSAIL system can mirror a user's motions and follow nonverbal commands by monitoring arm muscles.
Robotic sweepers, flappers, and telescoping arms face off for a shot at coveted engineering prize.
Tiny robots powered by magnetic fields could help drug-delivery nanoparticles reach their targets.
Model improves a robot’s ability to mold materials into shapes and interact with liquids and solid objects.
CSAIL’s "RoCycle" system uses in-hand sensors to detect if an object is paper, metal or plastic.
Through MIT Professional Education’s Advanced Study Program, Ernie Ho found the tools — and the community — he needed to realize his vision and launch his career.
Senior and Marshall Scholar Crystal Winston pursues her vision of a world where cars aren’t limited to roads.
Loosely connected disc-shaped “particles” can push and pull one another, moving en masse to transport objects.
Gripper device inspired by “origami magic ball” can grasp wide array of delicate and heavy objects.
Robot’s lightweight, high-power design is the perfect platform to share and play, developers say.