The technology uses tactile sensing to identify objects underground and might one day help disarm land mines or inspect cables.
Algorithm helps robot swarms complete missions with minimal wasted effort
Algorithm accepts or rejects each robot’s mission trajectory, depending on whether it increases or decreases the team’s objective function.
Radio frequency perception helps robot grasp hidden objects
MIT researchers have developed a robot that uses radio waves, which can pass through walls, to sense occluded objects. The robot, called RF-Grasp, combines this powerful sensing with more traditional computer vision to locate and grasp items that might otherwise be blocked from view. The advance could one day streamline e-commerce fulfillment in warehouses or…
Deep learning optimizes sensor placement for soft robots
There are some tasks traditional robots – the rigid and metallic kind – simply aren’t cut out for. Soft-bodied robots, on the other hand, may be able to interact with people more safely or slip into tight spaces with ease. But for robots to reliably complete their programmed duties, they need to know the whereabouts…
Soft actuator enables smaller, more agile drone design
New soft actuator can flap nearly 500 times per second, giving drones insect-like resilience.
‘Robomorphic computing’ aims to quicken robots’ response time
Contemporary robots can move quickly. “The motors are fast, and they’re powerful,” says Sabrina Neuman. Yet in complex situations, like interactions with people, robots often don’t move quickly. “The hang up is what’s going on in the robot’s head,” she adds. Perceiving stimuli and calculating a response takes a “boatload of computation,” which limits reaction…
RoboGrammar wants to automate your robot’s design
Robot design is still a very manual process, but MIT researchers can automate and optimize robot design with a system called RoboGrammar.
MIT neural network learns when it shouldn’t be trusted
Increasingly, artificial intelligence systems known as deep learning neural networks are used to inform decisions vital to human health and safety, such as in autonomous driving or medical diagnosis. These networks are good at recognizing patterns in large, complex datasets to aid in decision-making. But how do we know they’re correct? Alexander Amini and his…