robotics – MIT EECS

“DribbleBot” can maneuver a soccer ball on landscapes such as sand, gravel, mud, and snow, using reinforcement learning to adapt to varying ball dynamics.

Two rounded glass compartments, one holding a computer chip, frame a view of the Charles River.

The device could help scientists explore unknown regions of the ocean, track pollution, or monitor the effects of climate change.

This image shows 3D-printed crystalline lattice structures with air-filled channels, known as "fluidic sensors," embedded into the structures (the indents on the middle of lattices are the outlet holes of the sensors.) These air channels let the researchers measure how much force the lattices experience when they are compressed or flattened.

Engineers 3D print materials with networks of sensors directly incorporated.

CSAIL scientists came up with a learning pipeline for the four-legged robot that learns to run entirely by trial and error in simulation.

A four-legged robotic system for playing soccer on various terrains

MIT engineers build a battery-free, wireless underwater camera

New programmable materials can sense their own movements

3 Questions: How the MIT mini cheetah learns to run