Two studies find “self-supervised” models, which learn about their environment from unlabeled data, can show activity patterns similar to those of the mammalian brain.

Anyone who has ever tried to pack a family-sized amount of luggage into a sedan-sized trunk knows this is a hard problem. Robots struggle with dense packing tasks, too.

The prompt: Design a robot from scratch.
The result: A blueprint for a machine unlike any walking animal.

With Style2Fab, makers can rapidly customize models of 3D-printable objects, such as assistive devices, without hampering their functionality.

Produced with techniques borrowed from Japanese paper-cutting, the strong metal lattices are lighter than cork and have customizable mechanical properties.

With a new technique, a robot can reason efficiently about moving objects using more than just its fingertips.

A new technique helps a nontechnical user understand why a robot failed, and then fine-tune it with minimal effort to perform a task effectively.

SoftZoo is a soft robot co-design platform that can test optimal shapes and sizes for robotic performance in different environments.

MIT researchers exhibit a new advancement in autonomous drone navigation, using brain-inspired liquid neural networks that excel in out-of-distribution scenarios.