MIT researchers have developed a wireless, private way to monitor a person’s sleep postures — whether snoozing on their back, stomach, or sides — using reflected radio signals from a small device mounted on a bedroom wall.
Most new roboticists want to program their robots to solve interesting, complex tasks — but it turns out that just moving them through space without colliding with objects is more difficult than it sounds.
Deep learning systems are revolutionizing technology around us, from voice recognition that pairs you with your phone to autonomous vehicles that are increasingly able to see and recognize obstacles ahead. But much of this success involves trial and error when it comes to the deep learning networks themselves. A group of MIT researchers recently reviewed their contributions to a better theoretical understanding of deep learning networks, providing direction for the field moving forward.
Regina Barzilay, the Delta Electronics Professor in the Department of Electrical Engineering and Computer Science, and Tommi Jaakkola, the Thomas Siebel Professor of Electrical Engineering and Computer Science, join Ziv Bar-Joseph from Carnegie Mellon University for a project using machine learning to seek treatment for Covid-19.
For humans, it can be challenging to manipulate thin flexible objects like ropes, wires, or cables. But if these problems are hard for humans, they are nearly impossible for robots. As a cable slides between the fingers, its shape is constantly changing, and the robot’s fingers must be constantly sensing and adjusting the cable’s position and motion.
A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), in collaboration with Ava Robotics and the Greater Boston Food Bank (GBFB), designed a new robotic system that powerfully disinfects surfaces and neutralizes aerosolized forms of the coronavirus.
What seizes your attention at first glance might change with a closer look. That elephant dressed in red wallpaper might initially grab your eye until your gaze moves to the woman on the living room couch and the surprising realization that the pair appear to be sharing a quiet moment together.
One of the hottest topics in robotics is the field of soft robots, which utilizes squishy and flexible materials rather than traditional rigid materials. But soft robots have been limited due to their lack of good sensing. A good robotic gripper needs to feel what it is touching (tactile sensing), and it needs to sense the positions of its fingers (proprioception). Such sensing has been missing from most soft robots.
A team from CSAIL came up with a method that dials us closer to more seamless human-robot collaboration. The system, called “Conduct-A-Bot,” uses human muscle signals from wearable sensors to pilot a robot’s movement.
MIT researchers have designed a congestion-control scheme for wireless networks that could help reduce lag times and increase quality in video streaming, video chat, mobile gaming, and other web services.
