In the Media

MIT study shows the power of adaptive training tools, like a basketball hoop that shrinks and raises as you make shots.

New approach could spark an era of battery-free ocean exploration, with applications ranging from marine conservation to aquaculture.

Realtime Robotics has created a controller that helps robots safely move around on the fly.

Top row, L to R: Oliver, Corrigan-Gibbs, Chen. Bottom row, L to R: Yan, Ragan-Kelley   2020 has seen the addition of many new faculty members, including five recent hires within EECS. Learn

Augmented reality (AR) and virtual reality (VR) companies have been working for years on developing systems that can incorporate real-life objects into their digitized worlds. With that in mind, a team from MIT’s Computer Science and Artificial Intelligence Lab has developed a smart glove that can detect your hand pose, as well as distinguish between more than 30 different household objects.

System could help prevent robots from overwhelming human teammates with information.

Autonomous vehicles share sidewalk space with pedestrians in six-day trial in Singaporean public garden.

At the recent International Conference on Robotics and Automation, MIT researchers led by Daniela Rus, the Andrew and Erna Viterbi Professor in MIT’s Department of Electrical Engineering and Computer Science, presented a printable origami robot that folds itself up from a flat sheet of plastic when heated and measures about a centimeter from front to back. Read more.

The MIT DARPA Robotics Challenge Team led by Professor Rus Tedrake reached new heights in the June 5-6 international DARPA Robotics Challenge in Pomona California, as they nimbly programmed their Atlas robot to perform a wide range of tasks in one hour. The goal of the event was to develop mobile robots to perform useful tasks in disaster-relief situations — in response to the 2011 Fukushima nuclear disaster. Read more.

A computer vision enabled technology developed by a team of EECS faculty Bill Freeman and Frédo Durand and their students is enabling a new way to identify structural defects in objects. The group will report this latest work at the Conference on Computer Vision and Pattern Recognition in June. Read more.

Here’s one way to get kids excited about programming: a "robot garden" with dozens of fast-changing LED lights and more than 100 origami robots that can crawl, swim, and blossom like flowers. Read more.

In a paper appearing in a forthcoming issue of the International Journal of Robotics Research, Professors and member of the Learning and Intelligent Systems Group Leslie Kaelbling and Tomas Lozano Perez and EECS graduate student Lawson Wong show that a system using an off-the-shelf algorithm to aggregate different perspectives can recognize four times as many objects as one that uses a single perspective, while reducing the number of misidentifications. Read more.