Human-computer interaction

Popular Science reporter Charlotte Hu writes that MIT researchers have simulated an environment in which socially-aware robots are able to choose whether they want to help or hinder one another, as part of an effort to help improve human-robot interactions. “If you look at the vast majority of what someone says during their day, it has to do with what other [people] want, what they think, getting what that person wants out of another [person],” explains research scientist Andrei Barbu. “And if you want to get to the point where you have a robot inside someone’s home, understanding social interactions is incredibly important.”

MIT researchers have developed a new machine learning system that can help robots learn to perform certain social interactions, reports Brian Heater for TechCrunch. “Researchers conducted tests in a simulated environment, to develop what they deemed ‘realistic and predictable’ interactions between robots,” writes Heater. “In the simulation, one robot watches another perform a task, attempts to determine the goal and then either attempts to help or hamper it in that task.”

MIT researchers are using magnets to help improve control of prosthetic limbs, reports Emmett Smith for Mashable. “The researchers inserted magnetic beads into muscle tissue to track the specific movements of each muscle,” reports Smith. “That information is then transferred to the bionic limb, giving the users direct control over it.”

In this video, Mashable spotlights how MIT researchers have developed a new system that can 3-D print objects without human intervention. “The system works thanks to a software toolkit that lets you design custom blueprints,” Mashable explains.

CSAIL researchers have developed a new system, dubbed LaserFactory, that can print custom devices and robots without human intervention, reports Brian Heater for TechCrunch. “The system is comprised of a software kit and hardware platform designed to create structures and assemble circuitry and sensors for the machine,” Heater writes.

Boston Globe reporter Hiawatha Bray spotlights Pison Technology, an MIT startup that has developed a new gesture control system that can be used to manipulate “digital devices by intercepting the electronic traffic between our hands and our brains, and translating them into commands the machines can understand.”

In this video, Mashable spotlights how MIT researchers have developed an origami-inspired soft robotic gripper that can grasp a wide variety of objects. 

In an article for the Financial Times, Ashley Nunes, a research affiliate at MIT, writes about the Ethiopian Airlines crash and examines the limits of automation. “The more automated the system, the more crucial the human operator becomes,” writes Nunes. “That’s because automation doesn’t purge demand for human labour, instead it changes the type of labour needed.”

Fast Company reporter Mark Wilson writes that CSAIL researchers have developed a new soft robotic gripper that is modeled after a Venus flytrap. “Dubbed the Magic Ball, it’s a rubber and plastic structure that can contract around an object like an origami flower,” Wilson explains.

CSAIL researchers have developed a new robotic gripper that contains an origami skeleton, enabling the device to open and close like a flower and grasp a variety of delicate and heavy objects, reports James Vincent for The Verge “By combining this foldable skeleton with the soft exterior, we get the best of both worlds,” explains Prof. Daniela Rus, director of CSAIL.

TechCrunch reporter Brian Heater writes that researchers at CSAIL and Harvard have developed a soft robotic gripper that can both handle delicate objects and lift items up to 100 times its own weight. “The gripper itself is made of an origami-inspired skeletal structure, covered in either fabric or a deflated balloon,” explains Heater.

Boston Globe reporter Katie Johnston speaks with several MIT researchers about their work developing technology that is aimed at improving collaboration between humans and robots. Prof. Julie Shah notes that offloading easier decisions onto a machine “would allow people to focus on the parts of job that truly require human judgment and experience.”

CSAIL researchers have developed a technique that makes it possible to create 3-D motion sculptures from 2-D video, reports Jennifer Kite-Powell for Forbes. The new technique could “open up the possibility to study social disorders, interpersonal interactions and team dynamics,” Kite-Powell explains.

BBC Click reports on a system developed by CSAIL researchers that creates 3-D motion sculptures based off of 2-D video. The technique, say the researchers, “could help dancers and athletes learn more about how they move.”

Writing for Forbes, Joseph Coughlin, director of the MIT AgeLab, examines the increasing influence of AI in our lives. Coughlin concludes that in the absence of a human alternative, brief interactions could change our perception of an AI system from “a simple tool that ‘does stuff’ around the house, to a presence that is a real part of our social self.”