Julie Shah, the Boeing Career Development Assistant Professor of Aeronautics and Astronautics at MIT and a principal investigator at CSAIL, is looking to enable more human-robot coordination on the factory floor. Today robots and humans are strictly segregated in an effort ensure safety, but Shah believes that by developing better planning tools for robots, humans and robots should be able to work together to increase efficiency.
Researchers have created a method to help workers collaborate with artificial intelligence systems.
When Olivier Chatot attended the Humanoid Robotics Competition during IAP last year, he was interested in learning how to program a robot to move and fight. He didn’t expect that the class would lead to a UROP at CSAIL continuing his IAP class project, working on the Little Dog research project, or playing a key role in teaching this year’s IAP course.
In a 1999 paper, Erik Demaine — now a CSAIL principal investigator, but then an 18-year-old PhD student at the University of Waterloo, in Canada — described an algorithm that could determine how to fold a piece of paper into any conceivable 3-D shape. It was a milestone paper in the field of computational origami, but the algorithm didn’t yield very practical folding patterns. Essentially, it took a very long strip of paper and wound it into the desired shape. The resulting structures tended to have lots of seams where the strip doubled back on itself, so they weren’t very sturdy.
By enabling users to easily create social apps that serve communities’ needs, the Graffiti framework aims to promote healthier online interactions.
Three new papers, co-authored by Associate Professor Manolis Kellis (head of the Computational Biology Group at CSAIL), appeared in the March 23 edition of Nature reporting three large studies of gene regulation in the human and fly genomes.
A certain type of artificial intelligence agent can learn the cause-and-effect basis of a navigation task during training.
MIT researchers and industry partners release white paper on designing accountable, traceable systems to enable respectful handling of personal financial data.
The series aims to help policymakers create better oversight of AI in society.
With new approach, researchers specify desired properties of a material, and a computer system generates a structure accordingly.