The digitization of practically everything coupled with the mobile Internet, the automation of knowledge work, and advanced robotics promises a future with democratized use of machines and wide-spread use of robots and customization. However, pervasive use of robots remains a hard problem. For any give task, the body of the robot has to be able to execute the task and the brain of the robot has to be able to control the body to deliver on that task. How can we accelerate the creation of robots customized to specific tasks? Where are the gaps that we need to address in order to advance toward a future where robots are common in the world and they help reliably with physical tasks? What are the roles of design, fabrication, and control along this trajectory?
In this talk Prof. Rus will discuss the use of computational design and fabrication toward pervasive use of robots. Prof. Rus will introduce recent developments in algorithms for customizing robots, focusing on a suite of algorithms for automatically designing, fabricating, and tasking robots using modularity, soft materials, and print-and-fold approaches. She will also describe how computation can play a role in creating robots more capable of reasoning in the world. By enabling on-demand creation of robots, we can begin to imagine a world with one robot for every physical task.
Dr. Daniela Rus is the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. She serves as the Director of the Toyota-CSAIL Joint Research Center and is a member of the science advisory board of the Toyota Research Institute. Rus' research interests are in robotics, mobile computing, and data science. Rus is a Class of 2002 MacArthur Fellow, a fellow of ACM, AAAI and IEEE, and a member of the National Academy of Engineering and the American Academy of Arts and Sciences. She is the recipient of the 2017 Engelberger Robotics Award from the Robotics Industries Association. She earned her PhD in Computer Science from Cornell University.