The hub of the local robotics industry
MassRobotics, a nonprofit founded by several MIT alumni, is advancing an industry that will play an increasingly important role in our lives.
MassRobotics, a nonprofit founded by several MIT alumni, is advancing an industry that will play an increasingly important role in our lives.
This robotic system uses radio frequency signals, computer vision, and complex reasoning to efficiently find items hidden under a pile.
A new system lets robots manipulate soft, deformable material into various shapes from visual inputs, which could one day enable better home assistants.
Ritu Raman leads the Raman Lab, where she creates adaptive biological materials for applications in medicine and machines.
MIT scientists unveil the first open-source simulation engine capable of constructing realistic environments for deployable training and testing of autonomous vehicles.
A new general-purpose optimizer can speed up the design of walking robots, self-driving vehicles, and other autonomous systems.
Inspired by fireflies, researchers create insect-scale robots that can emit light when they fly, which enables motion tracking and communication.
Thousands of children participate in MIT-developed artificial intelligence curriculum.
With modular components and an easy-to-use 3D interface, this interactive design pipeline enables anyone to create their own customized robotic hand.
In person for the first time in three years, the 2.007 (Design and Manufacturing I) Robot Competition celebrated its founder.
The TESSERAE project, a design for self-assembling space structures and habitats, has sent prototypes to the International Space Station.
Scientists have created a design and fabrication tool for soft pneumatic actuators for integrated sensing, which can power personalized health care, smart homes, and gaming.
A new neural network approach captures the characteristics of a physical system’s dynamic motion from video, regardless of rendering configuration or image differences.
Researchers have developed a technique that enables a robot to learn a new pick-and-place task with only a handful of human demonstrations.
MIT engineers Edward Adelson and Sandra Liu duo develop a robotic gripper with rich sensory capabilities.